Release notes
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
Version 1.23.4 (November 8, 2024)
Fixed
- Fixed
UnsupportedNonlinearOperator
error for the single argumentLinearAlgebra.norm
(#3864) - Fixed printing
MOI.Interval
withMIME"text/latex"
(#3866)
Other
- Various minor improvements to the documentation (#3855) (#3860)
- Added MathOptAI.jl and MathOptSymbolicAD.jl to the list of extensions in the documentation (#3858)
- Clarified
add_to_expression!
can add two expressions (#3859) - Added
SHOT
to the installation table (#3853) - Improvements to test coverage (#3867) (#3868) (#3869) (#3870) (#3871) (#3872) (#3873) (#3874) (#3875)
- JuMP now uses
MOI.add_constrained_variable
when adding a scalar variable with bounds for improving model creation performance with some solvers (#3863) (#3865)
Version 1.23.3 (October 21, 2024)
Fixed
- Fixed a printing bug with scientific numbers in
MIME"text/latex"
(#3838) - Fixed support for
AbstractString
inset_attribute
(#3840) - Fixed a bug reporting vector-valued duals in
solution_summary
(#3846) - Fixed
solution_summary
when there are duplicate variable and constraint names (#3848)
Other
- Documentation improvements (#3828) (#3831) (#3841) (#3843) (#3845)
- Added the tutorial Tolerances and numerical issues (#3829) (#3830) (#3835)
- Improved the Benders decomposition tutorial (#38232) (#3833) (#3834)
- Added
DifferentiationInterface.jl
to Automatic differentiation of user-defined operators (#3836) (#3842) - Added the tutorial Writing a solver interface (#3844)
- Added the section Debugging performance problems (#3850)
- Formatting improvements (#3849)
Version 1.23.2 (September 13, 2024)
Fixed
- Fixed an illegal simplification in
MA.operate!!
forNonlinearExpr
(#3826)
Other
- Added Rolling horizon problems tutorial (#3815)
- Added more tests for shapes and dual shapes (#3816)
- Added more packages to
extension-tests.yml
(#3817) (#3818) - Removed an unnecessary test(#3819)
- Documentation improvements (#3820) (#3822) (#3823)
- Added PiecewiseLinearOpt.jl to the docs (#3824)
Version 1.23.1 (August 30, 2024)
Fixed
- Fixed a bug with indicator constraints and the
in set
syntax (#3813)
Other
- Updated packages in documentation (#3807)
- Updated the transitioning from MATLAB tutorial (#3809)
- Add tutorial Performance problems with sum-if formulations (#3810)
Version 1.23.0 (August 13, 2024)
Added
Fixed
- Fixed a method for calling
value
on a::Number
(#3776) - Fixed querying dual of Symmetric and Hermitian equality constraints (#3797)
- Fixed
read_from_file
for coefficient types other thanFloat64
(#3801)
Other
- Documentation improvements
- Fixed missing character in installation instructions (#3777)
- Added a section of querying the Jacobian (#3779)
- Clarify that SCIP does not support lazy constraints (#3784)
- Fixed typo in
knapsack.jl
(#3792) - Added a warning to docs about tolerances in Bin and Int variables (#3794)
- Clarify where to type installation commands (#3795)
- Improve error message for common incorrect syntax in constraint macro (#3781)
- Changed
show(::IO, ::GenericModel)
to a more informative tree structure (#3803)
Version 1.22.2 (June 17, 2024)
Fixed
- Fixed printing to omit terms when printing a large array of expressions (#3759)
- Fixed bug in printing when
show
is called on an invalid variable or constraint (#3763)
Other
- Improved error message for unsupported
kwargs
in variable macro (#3751) - Improved error message for unsupported container syntax like
x[A][B]
(#3756) - Docstring improvements (#3758), (#3760), (#3761), (#3767)
- Added warning to documentation about
Y <= X, Set()
syntax (#3769) - Work-around change on
nightly
(#3753), (#3754) - Improved printing of symmetric matrices when used in constraints (#3768)
- Fixed a test for upcoming printing change in MOI (#3772)
- Updated
should_i_use.md
(#3773)
Version 1.22.1 (May 17, 2024)
Fixed
- Fixed bug including non-
.jl
files insrc/macros.jl
(#3747)
Other
Version 1.22.0 (May 12, 2024)
Added
- Added
Base.complex(r, i)
wherer
andi
may be real-valued variables or affine or quadratic expressions (#3734) - Added
@force_nonlinear
for controlling when affine and quadratic expressions are instead parsed as nonlinear expressions. This can be useful for advanced users in a limited set of circumstances. (#3732) - Added support for returning the variable coefficients of a vector-valued constraint via
normalized_coefficient
. In addition,set_normalized_coefficients
has been softly deprecated (no warning is thrown and old code will still work for all future 1.X releases of JuMP) in favor ofset_normalized_coefficient
. This change was made to unify how we get and set variable coefficients. (#3743)
Fixed
- Fixed missing
promote_operation
method that resulted in slow code (#3730) - Improved performance of
getindex
forContainers.DenseAxisArray
(#3731) - Fixed the error message when the legacy nonlinear API is mixed with the new nonlinear API. In particular, we now uniformly throw an error message when unexpected objects occur in nonlinear expressions. (#3741)
Other
Version 1.21.1 (April 11, 2024)
Fixed
- Fixed behavior of complex-value related functions like
real
,imag
,conj
andabs2
when called onGenericNonlinearExpr
. This fixes a method error when callingx'
wherex
is an array of nonlinear expressions. As a related consequence, we now always error when creating nonlinear expressions with complex components. Previously, only some constructors were checked for complex expressionns. (#3724)
Other
Version 1.21.0 (March 31, 2024)
Added
- Added support for matrix inequality constraints with the
HermitianPSDCone
(#3705) - Added batched modification methods for
set_normalized_rhs
,set_objective_coefficient
andset_normalized_coefficient
. Using these methods can be more efficient for some solvers (#3716) - Added the private constant
_CONSTRAINT_LIMIT_FOR_PRINTING
, which controls how many constraints are printed to the screen duringprint(model)
. The main purpose of this is to prevent large quantities of text being printed whenprint(model)
is accidentally called on a large model. (#3686)
Fixed
- Changed
Containers.SparseAxisArray
to use anOrderedDict
as the backing data structure. Iterating over the elements in aSparseAxisArray
now iterates in the order that the elements were created. Previously, the order was undefined behavior. (#3681) - Fixed complex variables for non-Float64 coefficient types (#3691)
- Fixed
LinearAlgebra.hermitan(::AbstractJuMPScalar)
(#3693) - Fixed multiplying real scalar by Hermitian matrix (#3695)
Other
- Documentation improvements (#3679) (#3683) (#3702) (#3703) (#3706) (#3696) (#3708) (#3709) (#3711)
- Added new tutorials:
- Updated versions and compat bounds (#3687) (#3707) (#3717)
Version 1.20.0 (February 15, 2024)
Added
- Added
is_solved_and_feasible
(#3668) - Added support for
MOI.ModelLike
as the optimizer (#3667)
Fixed
Other
Version 1.19.0 (February 1, 2024)
Added
- Added support for modifying quadratic coefficients (#3658)
Fixed
- Fixed short circuiting of
&&
and||
in macros (#3655)
Other
- Added SDPLR to list of solvers (#3644)
- Added new roadmap items (#3645)
- Fixed vale.sh version (#3650)
- Improve error messages in macros (#3653)
- Refactoring of
set_normalized_coefficient
(#3660) (#3661) - Update
docs/packages.toml
(#3662)
Version 1.18.1 (January 6, 2024)
Fixed
Version 1.18.0 (January 2, 2024)
Added
- This release includes a large refactoring of the macro code that closes a roadmap item (#3629) Contributing pull requests include (#3600), (#3603), (#3606), (#3607), (#3610), (#3611), (#3612), (#3613), (#3614), (#3615), (#3617), (#3618), (#3619), (#3620), (#3621), (#3631), (#3632), (#3633)
Fixed
- Fixed error for unsupported objective sense (#3601)
- Fixed
text/latex
printing ofGenericNonlinearExpr
(#3609) - Fixed compat bounds of
stdlib
packages (#3626) - Fixed a bug that can accidentally modify the user's expressions in a macro (#3639)
- Fixed a bug converting
AffExpr
toGenericNonlinearExpr
(#3642)
Other
- Added
DisjunctiveProgramming
toextension-tests
(#3597) - Added
DisjunctiveProgramming
to docs (#3598) - Added DocumenterCitations to the docs (#3596), (#3630)
- Migrate from SnoopPrecompile to PrecompileTools (#3608)
- Minor documentation updates (#3623), (#3628), (#3635), (#3640), (#3643)
Version 1.17.0 (December 4, 2023)
Added
- Added
start_value
,lower_bound
, andupper_bound
support forGenericAffExpr
that are equivalent to a singleGenericVariableRef
(#3551) - Added
SkipModelConvertScalarSetWrapper
which is useful for extensions looking to avoidmodel_convert
(#3552) (#3592) - Added
lp_matrix_data
(#3573) (#3591)
Fixed
- Fixed
variable_ref_type
for unsupported types (#3556) - Fixed convert type of constraint starting values (#3571)
- Fixed various methods to support
AbstractJuMPScalar
withDistances.jl
(#3583) - Fixed
eachindex
for multiple arguments ofContainers.DenseAxisArray
andContainers.SparseAxisArray
(#3587) - Expressions with more than 60 terms now print in truncated form. This prevents large expressions from being accidentally printed to terminal or IJulia output (#3575)
- Fixed a type instability in
set_objective_coefficient
(#3590) - Various fixes to the documentation (#3593) (#3595)
Other
- Improved error messages for:
- Added new solvers to the documentation:
- Added new tutorials:
- Improved documentation for:
Semicontinuous
andSemiinteger
variables (#3562)SOS1
andSOS2
(#3565)start_value
ofHermitianPSDCone
(#3564)- Function tracing (#3570)
- Nonlinear operators with vector arguments (#3577)
- Indicator constraints (#3582)
- Updated package compat bounds (#3578)
Version 1.16.0 (October 24, 2023)
Added
- Added
:=
operator for Boolean satisfiability problems (#3530)
Fixed
- Fixed
text/latex
printing ofMOI.Interval
sets (#3537) - Fixed tests with duplicate function names (#3539)
Other
- Updated documentation list of supported solvers (#3527) (#3529) (#3538) (#3542) (#3545) (#3546)
- Updated to Documenter@1.1 (#3528)
- Fixed various tutorials (#3534) (#3532)
- Fixed
Project.toml
compat bounds for standard libraries (#3544)
Version 1.15.1 (September 24, 2023)
Fixed
- Fixed support for single argument
min
andmax
operators (#3522) - Fixed error message for
add_to_expression!
when called with aGenericNonlinearExpr
(#3506) - Fixed constraint tags with broadcasted constraints (#3515)
- Fixed MethodError in
MA.scaling
(#3518) - Fixed support for arrays of
Parameter
variables (#3524)
Other
- Updated to Documenter@1 (#3501)
- Fixed links to data in tutorials (#3512)
- Fixed typo in TSP tutorial (#3516)
- Improved error message for
VariableNotOwned
errors (#3520) - Fixed various JET errors (#3519)
Version 1.15.0 (September 15, 2023)
This is a large minor release because it adds an entirely new data structure and API path for working with nonlinear programs. The previous nonlinear interface remains unchanged and is documented at Nonlinear Modeling (Legacy). The new interface is a treated as a non-breaking feature addition and is documented at Nonlinear Modeling.
Breaking
Although the new nonlinear interface is a feature addition, there are two changes which might be breaking for a very small number of users.
- The syntax inside JuMP macros is parsed using a different code path, even for linear and quadratic expressions. We made this change to unify how we parse linear, quadratic, and nonlinear expressions. In all cases, the new code returns equivalent expressions, but because of the different order of operations, there are three changes to be aware of when updating:
- The printed form of the expression may change, for example from
x * y
toy * x
. This can cause tests which test theString
representation of a model to fail. - Some coefficients may change slightly due to floating point round-off error.
- Particularly when working with a JuMP extension, you may encounter a
MethodError
due to a missing or ambiguous method. These errors are due to previously existing bugs that were not triggered by the previous parsing code. If you encounter such an error, please open a GitHub issue.
- The printed form of the expression may change, for example from
- The methods for
Base.:^(x::VariableRef, n::Integer)
andBase.:^(x::AffExpr, n::Integer)
have changed. Previously, these methods supported onlyn = 0, 1, 2
and they always returned aQuadExpr
, even for the case whenn = 0
orn = 1
. Now:x^0
returnsone(T)
, whereT
is thevalue_type
of the model (defaults toFloat64
)x^1
returnsx
x^2
returns aQuadExpr
x^n
where!(0 <= n <= 2)
returns aNonlinearExpr
.
x^1
returned aQuadExpr
.) As a consequence of this change, the methods are now not type-stable. This means that the compiler cannot prove thatx^2
returns aQuadExpr
. If benchmarking shows that this is a performance problem, you can use the type-stablex * x
instead ofx^2
.
Added
- Added
triangle_vec
which simplifies addingMOI.LogDetConeTriangle
andMOI.RootDetConeTriangle
constraints (#3456) - Added the new nonlinear interface. This is a very large change. See the documentation at Nonlinear Modeling and the (long) discussion in JuMP.jl#3106. Related PRs are (#3468) (#3472) (#3475) (#3483) (#3487) (#3488) (#3489) (#3504) (#3509)
Fixed
- Fixed uses of
@nospecialize
which cause precompilation failures in Julia v1.6.0 and v1.6.1. (#3464) - Fixed adding a container of
Parameter
(#3473) - Fixed return type of
x^0
andx^1
to no longer returnQuadExpr
(see note inBreaking
section above) (#3474) - Fixed error messages in
LowerBoundRef
,UpperBoundRef
,FixRef
,IntegerRef
,BinaryRef
,ParameterRef
and related functions (#3494) - Fixed type inference of empty containers in JuMP macros (#3500)
Other
- Added GAMS to solver documentation (#3357)
- Updated various tutorials (#3459) (#3460) (#3462) (#3463) (#3465) (#3490) (#3492) (#3503)
- Added The network multi-commodity flow problem tutorial (#3491)
- Added Two-stage stochastic programs tutorial (#3466)
- Added better error messages for unsupported operations in
LinearAlgebra
(#3476) - Updated to the latest version of Documenter (#3484) (#3495) (#3497)
- Updated GitHub action versions (#3507)
Version 1.14.1 (September 2, 2023)
Fixed
- Fix links in Documentation (#3478)
Version 1.14.0 (August 27, 2023)
Added
- Added DimensionalData.jl extension (#3413)
- Added syntactic sugar for the
MOI.Parameter
set (#3443)
Fixed
- Fixed
model_convert
forBridgeableConstraint
(#3437) - Fixed printing models with integer coefficients larger than
typemax(Int)
(#3447) - Fixed support for constant left-hand side functions in a complementarity constraint (#3452)
Other
- Updated packages used in documentation (#3444) (#3455)
- Fixed docstring tests (#3445)
- Fixed printing change for MathOptInterface (#3446)
- Fixed typos in documentation (#3448) (#3457)
- Added SCIP to callback documentation (#3449)
Version 1.13.0 (July 27, 2023)
Added
- Added support for generic number types (#3377) (#3385)
- Added fallback for
MOI.AbstractSymmetricMatrixSetTriangle
andMOI.AbstractSymmetricMatrixSetSquare
(#3424)
Fixed
- Fixed
set_start_values
withMOI.Bridges.Objective.SlackBridge
(#3422) - Fixed flakey doctest in
variables.md
(#3425) - Fixed names on
CITATION.bib
(#3423)
Other
- Added Loraine.jl to the installation table (#3426)
- Removed Penopt.jl from packages.toml (#3428)
- Improved problem statement in cannery example of tutorial (#3430)
- Minor cleanups in
Containers.DenseAxisArray
implementation (#3429) - Changed
nested_problems.jl
: outer/inner to upper/lower (#3433) - Removed second SDP relaxation in OPF tutorial (#3432)
Version 1.12.0 (June 19, 2023)
Added
- Added
coefficient_type
keyword argument toadd_bridge
andremove_bridge
(#3394)
Fixed
- Fixed error message for matrix in
HermitianPSDCone
(#3369) - Fixed
EditURL
for custom documentation pages (#3373) - Fixed return type annotations for
MOI.ConstraintPrimal
andMOI.ConstraintDual
(#3381) - Fixed printing change in Julia nightly (#3391)
- Fixed printing of
Complex
coefficients (#3397) - Fixed printing of constraints in
text/latex
mode (#3405) - Fixed performance issue in
Containers.rowtable
(#3410) - Fixed bug when variables added to set of wrong dimension (#3411)
Other
- Added more solver READMEs to the documentation (#3358) (#3360) (#3364) (#3365) (#3366) (#3368) (#3372) (#3374) (#3376) (#3379) (#3387) (#3389)
- Added StatusSwitchingQP.jl to the installation table (#3354)
- Updated checklist for adding a new solver (#3370)
- Updated
extension-tests.yml
action (#3371) (#3375) - Color logs in GitHub actions (#3392)
- Added new tutorials
- Updated JuMP paper citation (#3400)
- Changed GitHub action to upload LaTeX logs when building documentation (#3403)
- Fixed printing of SCS log in documentation (#3406)
- Updated solver versions (#3407)
- Updated documentation to use Julia v1.9 (#3398)
- Replaced
_value_type
withMOI.Utilities.value_type
(#3414) - Fixed a typo in docstring (#3415)
- Refactored API documentation (#3386)
- Updated SCIP license (#3420)
Version 1.11.1 (May 19, 2023)
Fixed
- Fixed a poor error message when
sum(::DenseAxisArray; dims)
was called (#3338) - Fixed support for dependent sets in the
@variable
macro (#3344) - Fixed a performance bug in constraints with sparse symmetric matrices (#3349)
Other
- Improved the printing of complex numbers (#3332)
- When printing, sets which contain constants ending in
.0
now print as integers. This follows the behavior of constants in functions (#3341) - Added
InfiniteOpt
to the extensions documentation (#3343) - Added more documentation for the exponential cone (#3345) (#3347)
- Added checklists for developers (#3346) (#3355)
- Fixed test support upcoming Julia nightly (#3351)
- Fixed
extension-tests.yml
action (#3353) - Add more solvers to the documentation (#3359) (#3361) (#3362)
Version 1.11.0 (May 3, 2023)
Added
- Added new methods to
print_active_bridges
for printing a particular objective, constraint, or variable (#3316)
Fixed
- Fixed tests for MOI v1.14.0 release (#3312)
- Fixed indexing containers when an axis is
Vector{Any}
that contains aVector{Any}
element (#3280) - Fixed
getindex(::AbstractJuMPScalar)
which is called for an expression likex[]
(#3314) - Fixed bug in
set_string_names_on_creation
with a vector of variables (#3322) - Fixed bug in
memoize
function in nonlinear documentation (#3337)
Other
- Fixed typos in the documentation (#3317) (#3318) (#3328)
- Added a test for the order of setting start values (#3315)
- Added READMEs of solvers and extensions to the docs (#3309) (#3320) (#3327) (#3329) (#3333)
- Style improvements to
src/variables.jl
(#3324) - Clarify that column generation does not find global optimum (#3325)
- Add a GitHub actions workflow for testing extensions prior to release (#3331)
- Document the release process for JuMP (#3334)
- Fix links to discourse and chatroom (#3335)
Version 1.10.0 (April 3, 2023)
Added
- Added
Nonnegatives
,Nonpositives
andZeros
, and support vector-valued inequality syntax in the JuMP macros (#3273) - Added special support for
LinearAlgebra.Symmetric
andLinearAlgebra.Hermitian
matrices inZeros
constraints (#3281) (#3296) - Added
HermitianMatrixSpace
and theHermitian
tag for generating a matrix of variables that is Hermitian (#3292) (#3293) - Added
Semicontinuous
andSemiinteger
(#3302) - Added support for keyword indexing of containers (#3237)
Fixed
- Fixed
[compat]
bound for MathOptInterface inProject.toml
(#3272)
Other
- Split out the Nested optimization problems tutorial (#3274)
- Updated doctests to ensure none have hidden state (#3275) (#3276)
- Clarified how lazy constraints may revisit points (#3278)
- Added P-Norm example (#3282)
- Clarified docs that macros create new bindings (#3284)
- Fixed threading example (#3283)
- Added plot to The minimum distortion problem (#3288)
- Added Google style rules for Vale and fixed warnings (#3285)
- Added citation for the JuMP 1.0 paper (#3294)
- Updated package versions in the documentation (#3298)
- Added comment for the order in which start values must be set (#3303)
- Improved error message for unrecognized constraint operators (#3311)
Version 1.9.0 (March 7, 2023)
Added
- Added
get_attribute
andset_attribute
. These replaceget_optimizer_attribute
andset_optimizer_attribute
, although the_optimizer_
functions remain for backward compatibility. (#3219) - Added
set_start_values
for setting all supported start values in a model (#3238) - Add
remove_bridge
andprint_active_bridges
(#3259)
Fixed
- The matrix returned by a variable in
HermitianPSDCone
is now aLinearAlgebra.Hermitian
matrix. This is potentially breaking if you have written code to assume the return is aMatrix
. (#3245) (#3246) - Fixed missing support for
Base.isreal
of expressions (#3252)
Other
- Fixed a thread safety issue in the Parallelism tutorial (#3240) (#3243)
- Improved the error message when unsupported operators are used in
@NL
macros (#3236) - Clarified the documentation to say that matrices in
HermitianPSDCone
must beLinearAlgebra.Hermitian
(#3241) - Minor style fixes to internal macro code (#3247)
- Add Example: quantum state discrimination tutorial (#3250)
- Improve error message when
begin...end
not passed to plural macros (#3255) - Document how to register function with varying number of input arguments (#3258)
- Tidy tests by removing unneeded
JuMP.
prefixes (#3260) - Clarified the introduction to the Complex number support tutorial (#3262)
- Fixed typos in the Documentation (#3263) (#3266) (#3268) (#3269)
Version 1.8.2 (February 27, 2023)
Fixed
- Fixed dot product between complex JuMP expression and number (#3244)
Other
- Polish simple SDP examples (#3232)
Version 1.8.1 (February 23, 2023)
Fixed
- Fixed support for
init
in nonlinear generator expressions (#3226)
Other
- Use and document
import MathOptInterface as MOI
(#3222) - Removed references in documentation to multiobjective optimization being unsupported (#3223)
- Added tutorial on multi-objective portfolio optimization (#3227)
- Refactored some of the conic tutorials (#3229)
- Fixed typos in the documentation (#3230)
- Added tutorial on parallelism (#3231)
Version 1.8.0 (February 16, 2023)
Added
- Added
-->
syntax support for indicator constraints. The old syntax of=>
remains supported (#3207) - Added
<-->
syntax for reified constraints. For now, few solvers support reified constraints (#3206) - Added
fix_discrete_variables
. This is most useful for computing the dual of a mixed-integer program (#3208) - Added support for vector-valued objectives. For details, see the Multi-objective knapsack tutorial (#3176)
Fixed
- Fixed a bug in
lp_sensitivity_report
by switching to an explicit LU factorization of the basis matrix (#3182) - Fixed a bug that prevented
[; kwarg]
arguments in macros (#3220)
Other
- Minor fixes to the documentation (#3200) (#3201) (#3203) (#3210)
- Added tutorial Constraint programming (#3202)
- Added more examples to Modeling with cones
- Remove
_distance_to_set
in favor ofMOI.Utilities.distance_to_set
(#3209) - Improve The diet problem tutorial by adding the variable as a column in the dataframe (#3213)
- Improve The knapsack problem example tutorial (#3216) (#3217)
- Added the Example: ellipsoid approximation tutorial (#3218)
Version 1.7.0 (January 25, 2023)
Added
- Added support for
view
of aContainers.DenseAxisArray
(#3152) (#3180) - Added support for containers of variables in
ComplexPlane
(#3184) - Added support for
minimum
andmaximum
generators in nonlinear expressions (#3189) - Added
SnoopPrecompile
statements that reduce the time-to-first-solve in Julia 1.9 (#3193) (#3195) (#3196) (#3197)
Other
- Large refactoring of the tests (#3166) (#3167) (#3168) (#3169) (#3170) (#3171)
- Remove unreachable code due to
VERSION
checks (#3172) - Document how to test JuMP extensions (#3174)
- Fix method ambiguities in
Containers
(#3173) - Improve error message that is thrown when
=
is used instead of==
in the@constraint
macro (#3178) - Improve the error message when
Bool
is used instead ofBin
in the@variable
macro (#3180) - Update versions of the documentation (#3185)
- Tidy the import of packages and remove unnecessary prefixes (#3186) (#3187)
- Refactor
src/JuMP.jl
by moving methods into more relevant files (#3188) - Fix docstring of
Model
not appearing in the documentation (#3198)
Version 1.6.0 (January 1, 2023)
Added
- Added a
result
keyword argument tosolution_summary
to allow summarizing models with multiple solutions (#3138) - Added
relax_with_penalty!
, which is a useful tool when debugging infeasible models (#3140) - Added
has_start_value
(#3157) - Added support for
HermitianPSDCone
in constraints (#3154)
Fixed
Other
- Added Benders tutorial with in-place resolves (#3145)
- Added more Tips and tricks for linear programs (#3144) (#3163)
- Clarified documentation that
start
can depend on the indices of a variable container (#3148) - Replace instances of
length
andsize
by the recommendedeachindex
andaxes
(#3149) - Added a warning explaining why the model is dirty when accessing solution results from a modified model (#3156)
- Clarify documentation that
PSD
ensures a symmetric matrix (#3159) - Maintenance of the JuMP test suite (#3146) (#3158) (#3162)
Version 1.5.0 (December 8, 2022)
Added
- Add support for complex-valued variables:
- Add support for
MOI.OptimizerWithAttributes
inset_optimizer_attribute
andget_optimizer_attribute
(#3129)
Fixed
- Fixed error message for vectorized interval constraints (#3123)
- Fixed passing
AbstractString
toset_optimizer_attribute
(#3127)
Other
- Update package versions used in docs (#3119) (#3133) (#3139)
- Fixed output of diet tutorial (#3120)
- Explain how to use
Dates.period
inset_time_limit_sec
(#3121) - Update to
JuliaFormatter
v1.0.15 (#3130) - Fixed
HTTP
server example in web_app.jl (#3131) - Update docs to build with
Documenter#master
(#3094) - Add tests for
LinearAlgebra
operations (#3132) - Tidy these release notes (#3135)
- Added documentation for Complex number support (#3141)
- Removed the "workforce scheduling" and "steelT3" tutorials (#3143)
Version 1.4.0 (October 29, 2022)
Added
- Added
Containers.rowtable
which converts a container into a vector ofNamedTuple
s to support the Tables.jl interface. This simplifies convertingContainers.DenseAxisArray
andContainers.SparseAxisArray
objects into tabular forms such as a DataFrame (#3104) - Added a new method to
Containers.container
so that index names are passed to the container (#3088)
Fixed
- Fixed a bug in
copy_to(dest::Model, src::MOI.ModelLike)
whensrc
has nonlinear components (#3101) - Fixed the printing of
(-1.0 + 0.0im)
coefficients in complex expressions (#3112) - Fixed a parsing bug in nonlinear expressions with generator statements that contain multiple
for
statements (#3116)
Other
- Converted the multi-commodity flow tutorial to use an SQLite database (#3098)
- Fixed a number of typos in the documentation (#3103) (#3107) (#3018)
- Improved various style aspects of the PDF documentation (#3095) (#3098) (#3102)
Version 1.3.1 (September 28, 2022)
Fixed
- Fixed a performance issue in
relax_integrality
(#3087) - Fixed the type stability of operators with
Complex
arguments (#3072) - Fixed a bug which added additional
+()
terms to some nonlinear expressions (#3091) - Fixed potential method ambiguities with
AffExpr
andQuadExpr
objects (#3092)
Other
- Added vale as a linter for the documentation (#3080)
- Added a tutorial on debugging JuMP models (#3043)
- Fixed a number of typos in the documentation (#3079) (#3083)
- Many other small tweaks to the documentation (#3068) (#3073) (#3074) (#3075) (#3076) (#3077) (#3078) (#3081) (#3082) (#3084) (#3085) (#3089)
Version 1.3.0 (September 5, 2022)
Added
- Support slicing in
SparseAxisArray
(#3031)
Fixed
- Fixed a bug introduced in v1.2.0 that prevented
DenseAxisArray
s withVector
keys (#3064)
Other
- Released the JuMP logos under the CC BY 4.0 license (#3063)
- Minor tweaks to the documentation (#3054) (#3056) (#3057) (#3060) (#3061) (#3065)
- Improved code coverage of a number of files (#3048) (#3049) (#3050) (#3051) (#3052) (#3053) (#3058) (#3059)
Version 1.2.1 (August 22, 2022)
Fixed
- Fixed a bug when parsing two-sided nonlinear constraints (#3045)
Version 1.2.0 (August 16, 2022)
Breaking
This is a large minor release because it significantly refactors the internal code for handling nonlinear programs to use the MathOptInterface.Nonlinear
submodule that was introduced in MathOptInterface v1.3.0. As a consequence, the internal datastructure in model.nlp_data
has been removed, as has the JuMP._Derivatives
submodule. Despite the changes, the public API for nonlinear programming has not changed, and any code that uses only the public API and that worked with v1.1.1 will continue to work with v1.2.0.
Added
- Added
all_constraints(model; include_variable_in_set_constraints)
which simplifies returning a list of all constraint indices in the model. - Added the ability to delete nonlinear constraints via
delete(::Model, ::NonlinearConstraintRef)
. - Added the ability to provide an explicit Hessian for a multivariate user-defined function.
- Added support for querying the primal value of a nonlinear constraint via
value(::NonlinearConstraintRef)
Fixed
- Fixed a bug in
Containers.DenseAxisArray
so that it now supports indexing with keys that hash to the same value, even if they are different types, for example,Int32
andInt64
. - Fixed a bug printing the model when the solver does not support
MOI.Name
.
Other
- Added a constraint programming formulation to the Sudoku tutorial.
- Added newly supported solvers Pajarito, Clarabel, and COPT to the installation table.
- Fixed a variety of other miscellaneous issues in the documentation.
Version 1.1.1 (June 14, 2022)
Other
- Fixed problem displaying LaTeX in the documentation
- Minor updates to the style guide
- Updated to MOI v1.4.0 in the documentation
Version 1.1.0 (May 25, 2022)
Added
- Added
num_constraints(::Model; count_variable_in_set_constraints)
to simplify the process of counting the number of constraints in a model - Added
VariableRef(::ConstraintRef)
for querying the variable associated with a bound or integrality constraint. - Added
set_normalized_coefficients
for modifying the variable coefficients of a vector-valued constraint. - Added
set_string_names_on_creation
to disable creatingString
names for variables and constraints. This can improve performance.
Fixed
- Fixed a bug passing
nothing
to thestart
keyword of@variable
Other
- New tutorials:
- Sensitivity analysis of a linear program
- Serving web apps
- Minimal ellipse SDP tutorial refactored and improved
- Docs updated to the latest version of each package
- Lots of minor fixes and improvements to the documentation
Version 1.0.0 (March 24, 2022)
Read more about this release, along with an acknowledgement of all the contributors in our JuMP 1.0.0 is released blog post.
Breaking
- The previously deprecated functions (v0.23.0, v0.23.1) have been removed. Deprecation was to improve consistency of function names:
num_nl_constraints
(seenum_nonlinear_constraints
)all_nl_constraints
(seeall_nonlinear_constraints
)add_NL_expression
(seeadd_nonlinear_expression
)set_NL_objective
(seeset_nonlinear_objective
)add_NL_constraint
(seeadd_nonlinear_constraint
)nl_expr_string
(seenonlinear_expr_string
)nl_constraint_string
(seenonlinear_constraint_string
)SymMatrixSpace
(seeSymmetricMatrixSpace
)
- The unintentionally exported variable
JuMP.op_hint
has been renamed to the unexportedJuMP._OP_HINT
Fixed
- Fixed a bug writing .nl files
- Fixed a bug broadcasting
SparseAxisArray
s
Version 0.23.2 (March 14, 2022)
Added
- Added
relative_gap
tosolution_summary
register
now throws an informative error if the function is not differentiable using ForwardDiff. In some cases, the check inregister
will encounter a false negative, and the informative error will be thrown at run-time. This usually happens when the function is non-differentiable in a subset of the domain.
Fixed
- Fixed a scoping issue when extending the
container
keyword of containers
Other
- Docs updated to the latest version of each package
Version 0.23.1 (March 2, 2022)
Deprecated
nl_expr_string
andnl_constraint_string
have been renamed tononlinear_expr_string
andnonlinear_constraint_string
. The old methods still exist with deprecation warnings. This change should impact very few users because to call them you must rely on private internals of the nonlinear API. Users are encouraged to usesprint(show, x)
instead, wherex
is the nonlinear expression or constraint of interest.
Added
- Added support for
Base.abs2(x)
wherex
is a variable or affine expression. This is mainly useful for complex-valued constraints.
Fixed
- Fixed addition of complex and real affine expressions
- Fixed arithmetic for Complex-valued quadratic expressions
- Fixed variable bounds passed as
Rational{Int}(Inf)
- Fixed printing of the coefficient
(0 + 1im)
- Fixed a bug when
solution_summary
is called prior tooptimize!
Version 0.23.0 (February 25, 2022)
JuMP v0.23.0 is a breaking release. It is also a release-candidate for JuMP v1.0.0. That is, if no issues are found with the v0.23.0 release, then it will be re-tagged as v1.0.0.
Breaking
- Julia 1.6 is now the minimum supported version
- MathOptInterface has been updated to v1.0.0
- All previously deprecated functionality has been removed
PrintMode
,REPLMode
andIJuliaMode
have been removed in favor of the MIME typesMIME"text/plain"
andMIME"text/latex"
. Replace instances of::Type{REPLMode}
with::MIME"text/plain"
,REPLMode
withMIME("text/plain")
,::Type{IJuliaMode}
with::MIME"text/latex"
, andIJuliaMode
withMIME("text/latex")
.- Functions containing the
nl_
acronym have been renamed to the more explicitnonlinear_
. For example,num_nl_constraints
is nownum_nonlinear_constraints
andset_NL_objective
is nowset_nonlinear_objective
. Calls to the old functions throw an error explaining the new name. SymMatrixSpace
has been renamed toSymmetricMatrixSpace
Added
- Added
nonlinear_dual_start_value
andset_nonlinear_dual_start_value
- Added preliminary support for
Complex
coefficient types
Fixed
- Fixed a bug in
solution_summary
Other
- MILP examples have been migrated from GLPK to HiGHS
- Fixed various typos
- Improved section on setting constraint start values
Troubleshooting problems when updating
If you experience problems when updating, you are likely using previously deprecated functionality. (By default, Julia does not warn when you use deprecated features.)
To find the deprecated features you are using, start Julia with --depwarn=yes
:
$ julia --depwarn=yes
Then install JuMP v0.22.3:
julia> using Pkg
julia> pkg"add JuMP@0.22.3"
And then run your code. Apply any suggestions, or search the release notes below for advice on updating a specific deprecated feature.
Version 0.22.3 (February 10, 2022)
Fixed
- Fixed a reproducibility issue in the TSP tutorial
- Fixed a reproducibility issue in the
max_cut_sdp
tutorial - Fixed a bug broadcasting an empty SparseAxisArray
Other
- Added a warning and improved documentation for the modify-then-query case
- Fixed a typo in the docstring of
RotatedSecondOrderCone
- Added Aqua.jl as a check for code health
- Added introductions to each section of the tutorials
- Improved the column generation and Benders decomposition tutorials
- Updated documentation to MOI v0.10.8
- Updated JuliaFormatter to v0.22.2
Version 0.22.2 (January 10, 2022)
Added
- The function
all_nl_constraints
now returns all nonlinear constraints in a model start_value
andset_start_value
can now be used to get and set the primal start for constraint references- Plural macros now return a tuple containing the elements that were defined instead of
nothing
- Anonymous variables are now printed as
_[i]
wherei
is the index of the variable instead ofnoname
. Callingname(x)
still returns""
so this is non-breaking.
Fixed
- Fixed handling of
min
andmax
in nonlinear expressions - CartesianIndex is no longer allowed as a key for DenseAxisArrays.
Other
- Improved the performance of GenericAffExpr
- Added a tutorial on the Travelling Salesperson Problem
- Added a tutorial on querying the Hessian of a nonlinear program
- Added documentation on using custom solver binaries.
Version 0.22.1 (November 29, 2021)
Added
- Export
OptimizationSense
enum, with instances:MIN_SENSE
,MAX_SENSE
, andFEASIBILITY_SENSE
- Add
Base.isempty(::Model)
to matchBase.empty(::Model)
Fixed
- Fix bug in container with tuples as indices
- Fix bug in
set_time_limit_sec
Other
- Add tutorial "Design patterns for larger models"
- Remove release notes section from PDF
- General edits of the documentation and error messages
Version 0.22.0 (November 10, 2021)
JuMP v0.22 is a breaking release
Breaking
JuMP 0.22 contains a number of breaking changes. However, these should be invisible for the majority of users. You will mostly encounter these breaking changes if you: wrote a JuMP extension, accessed backend(model)
, or called @SDconstraint
.
The breaking changes are as follows:
- MathOptInterface has been updated to v0.10.4. For users who have interacted with the MOI backend, this contains a large number of breaking changes. Read the MathOptInterface release notes for more details.
- The
bridge_constraints
keyword argument toModel
andset_optimizer
has been renamedadd_bridges
to reflect that more thing were bridged than just constraints. - The
backend(model)
field now contains a concrete instance of aMOI.Utilities.CachingOptimizer
instead of one with an abstractly typed optimizer field. In most cases, this will lead to improved performance. However, callingset_optimizer
afterbackend
invalidates the old backend. For example:model = Model() b = backend(model) set_optimizer(model, GLPK.Optimizer) @variable(model, x) # b is not updated with `x`! Get a new b by calling `backend` again. new_b = backend(model)
- All usages of
@SDconstraint
are deprecated. The new syntax is@constraint(model, X >= Y, PSDCone())
. - Creating a
DenseAxisArray
with aNumber
as an axis will now display a warning. This catches a common error in which users write@variable(model, x[length(S)])
instead of@variable(model, x[1:length(S)])
. - The
caching_mode
argument toModel
, for example,Model(caching_mode = MOIU.MANUAL)
mode has been removed. For more control over the optimizer, usedirect_model
instead. - The previously deprecated
lp_objective_perturbation_range
andlp_rhs_perturbation_range
functions have been removed. Uselp_sensitivity_report
instead. - The
.m
fields ofNonlinearExpression
andNonlinearParameter
have been renamed to.model
. - Infinite variable bounds are now ignored. Thus,
@variable(model, x <= Inf)
will showhas_upper_bound(x) == false
. Previously, these bounds were passed through to the solvers which caused numerical issues for solvers expecting finite bounds. - The
variable_type
andconstraint_type
functions were removed. This should only affect users who previously wrote JuMP extensions. The functions can be deleted without consequence. - The internal functions
moi_mode
,moi_bridge_constraints
,moi_add_constraint
, andmoi_add_to_function_constant
are no longer exported. - The un-used method
Containers.generate_container
has been deleted. - The
Containers
API has been refactored, and_build_ref_sets
is now public asContainers.build_ref_sets
. - The
parse_constraint_
methods for extending@constraint
at parse time have been refactored in a breaking way. Consult the Extensions documentation for more details and examples.
Added
- The
TerminationStatusCode
andResultStatusCode
enums are now exported by JuMP. Prefertermination_status(model) == OPTIMAL
instead of== MOI.OPTIMAL
, although theMOI.
prefix way still works. - Copy a
x::DenseAxisArray
to anArray
by callingArray(x)
. NonlinearExpression
is now a subtype ofAbstractJuMPScalar
- Constraints such as
@constraint(model, x + 1 in MOI.Integer())
are now supported. primal_feasibility_report
now accepts a function as the first argument.- Scalar variables
@variable(model, x[1:2] in MOI.Integer())
creates two variables, both of which are constrained to be in the setMOI.Integer
. - Conic constraints can now be specified as inequalities under a different partial ordering. So
@constraint(model, x - y in MOI.Nonnegatives())
can now be written as@constraint(model, x >= y, MOI.Nonnegatives())
. - Names are now set for vectorized constraints.
Fixed
- Fixed a performance issue when
show
was called on aSparseAxisArray
with a large number of elements. - Fixed a bug displaying barrier and simplex iterations in
solution_summary
. - Fixed a bug by implementing
hash
forDenseAxisArray
andSparseAxisArray
. - Names are now only set if the solver supports them. Previously, this prevented solvers such as Ipopt from being used with
direct_model
. MutableArithmetics.Zero
is converted into a0.0
before being returned to the user. Previously, some calls to@expression
would return the undocumentedMutableArithmetics.Zero()
object. One example is summing over an empty set@expression(model, sum(x[i] for i in 1:0))
. You will now get0.0
instead.AffExpr
andQuadExpr
can now be used with== 0
instead ofiszero
. This fixes a number of issues relating to Julia standard libraries such asLinearAlgebra
andSparseArrays
.- Fixed a bug when registering a user-defined function with splatting.
Other
- The documentation is now available as a PDF.
- The documentation now includes a full copy of the MathOptInterface documentation to make it easy to link concepts between the docs. (The MathOptInterface documentation has also been significantly improved.)
- The documentation contains a large number of improvements and clarifications on a range of topics. Thanks to @sshin23, @DilumAluthge, and @jlwether.
- The documentation is now built with Julia 1.6 instead of 1.0.
- Various error messages have been improved to be more readable.
Version 0.21.10 (September 4, 2021)
Added
- Added
add_NL_expression
add_NL_xxx
functions now supportAffExpr
andQuadExpr
as terms
Fixed
- Fixed a bug in
solution_summary
- Fixed a bug in
relax_integrality
Other
- Improved error message in
lp_sensitivity_report
Version 0.21.9 (August 1, 2021)
Added
- Containers now support arbitrary container types by passing the type to the
container
keyword and overloadingContainers.container
. is_valid
now supports nonlinear constraints- Added
unsafe_backend
for querying the inner-most optimizer of a JuMP model. - Nonlinear parameters now support the plural
@NLparameters
macro. - Containers (for example,
DenseAxisArray
) can now be used in vector-valued constraints.
Other
- Various improvements to the documentation.
Version 0.21.8 (May 8, 2021)
Added
- The
@constraint
macro is now extendable in the same way as@variable
. AffExpr
andQuadExpr
can now be used in nonlinear macros.
Fixed
- Fixed a bug in
lp_sensitivity_report
. - Fixed an inference issue when creating empty
SparseAxisArray
s.
Version 0.21.7 (April 12, 2021)
Added
- Added
primal_feasibility_report
, which can be used to check whether a primal point satisfies primal feasibility. - Added
coefficient
, which returns the coefficient associated with a variable in affine and quadratic expressions. - Added
copy_conflict
, which returns the IIS of an infeasible model. - Added
solution_summary
, which returns (and prints) a struct containing a summary of the solution. - Allow
AbstractVector
in vector constraints instead of justVector
. - Added
latex_formulation(model)
which returns an object representing the latex formulation of a model. Useprint(latex_formulation(model))
to print the formulation as a string. - User-defined functions in nonlinear expressions are now automatically registered to aid quick model prototyping. However, a warning is printed to encourage the manual registration.
- DenseAxisArray's now support broadcasting over multiple arrays.
- Container indices can now be iterators of
Base.SizeUnknown
.
Fixed
- Fixed bug in
rad2deg
anddeg2rad
in nonlinear expressions. - Fixed a MethodError bug in
Containers
when forcing container type. - Allow partial slicing of a DenseAxisArray, resolving an issue from 2014.
- Fixed a bug printing variable names in IJulia.
- Ending an IJulia cell with
model
now prints a summary of the model (like in the REPL) not the latex formulation. Useprint(model)
to print the latex formulation. - Fixed a bug when copying models containing nested arrays.
Other
- Tutorials are now part of the documentation, and more refactoring has taken place.
- Added JuliaFormatter added as a code formatter.
- Added some precompilation statements to reduce initial latency.
- Various improvements to error messages to make them more helpful.
- Improved performance of
value(::NonlinearExpression)
. - Improved performance of
fix(::VariableRef)
.
Version 0.21.6 (January 29, 2021)
Added
- Added support for skew symmetric variables via
@variable(model, X[1:2, 1:2] in SkewSymmetricMatrixSpace())
. lp_sensitivity_report
has been added which significantly improves the performance of querying the sensitivity summary of an LP.lp_objective_perturbation_range
andlp_rhs_perturbation_range
are deprecated.- Dual warm-starts are now supported with
set_dual_start_value
anddual_start_value
. ∈
(\in<tab>
) can now be used in macros instead of=
orin
.- Use
haskey(model::Model, key::Symbol)
to check if a namekey
is registered in a model. - Added
unregister(model::Model, key::Symbol)
to unregister a namekey
frommodel
. - Added
callback_node_status
for use in callbacks. - Added
print_bridge_graph
to visualize the bridging graph generated by MathOptInterface. - Improved error message for containers with duplicate indices.
Fixed
- Various fixes to pass tests on Julia 1.6.
- Fixed a bug in the printing of nonlinear expressions in IJulia.
- Fixed a bug when nonlinear expressions are passed to user-defined functions.
- Some internal functions that were previously exported are now no longer exported.
- Fixed a bug when relaxing a fixed binary variable.
- Fixed a
StackOverflowError
that occurred whenSparseAxisArray
s had a large number of elements. - Removed an unnecessary type assertion in
list_of_constraint_types
. - Fixed a bug when copying models with registered expressions.
Other
- The documentation has been significantly overhauled. It now has distinct sections for the manual, API reference, and examples. The existing examples in
/examples
have now been moved to/docs/src/examples
and rewritten usingLiterate.jl
, and they are now included in the documentation. - JuliaFormatter has been applied to most of the codebase. This will continue to roll out over time, as we fix upstream issues in the formatter, and will eventually become compulsory.
- The root cause of a large number of method invalidations has been resolved.
- We switched continuous integration from Travis and Appveyor to GitHub Actions.
Version 0.21.5 (September 18, 2020)
Fixed
- Fixed deprecation warnings
- Throw
DimensionMismatch
for incompatibly sized functions and sets - Unify treatment of
keys(x)
on JuMP containers
Version 0.21.4 (September 14, 2020)
Added
- Add debug info when adding unsupported constraints
- Add
relax_integrality
for solving continuous relaxation - Allow querying constraint conflicts
Fixed
- Dispatch on
Real
forMOI.submit
- Implement
copy
forCustomSet
in tests - Don't export private macros
- Fix invalid assertion in nonlinear
- Error if constraint has
NaN
right-hand side - Improve speed of tests
- Lots of work modularizing files in
/test
- Improve line numbers in macro error messages
- Print nonlinear subexpressions
- Various documentation updates
- Dependency updates:
- Datastructures 0.18
- MathOptFormat v0.5
- Prep for MathOptInterface 0.9.15
Version 0.21.3 (June 18, 2020)
- Added Special Order Sets (SOS1 and SOS2) to JuMP with default weights to ease the creation of such constraints (#2212).
- Added functions
simplex_iterations
,barrier_iterations
andnode_count
(#2201). - Added function
reduced_cost
(#2205). - Implemented
callback_value
for affine and quadratic expressions (#2231). - Support
MutableArithmetics.Zero
in objective and constraints (#2219). - Documentation improvements:
- Containers improvements:
- Extensibility improvements:
Version 0.21.2 (April 2, 2020)
- Added
relative_gap()
to accessMOI.RelativeGap()
attribute (#2199). - Documentation fixes:
- Implementation of methods for Base functions:
Fixed
- Fixed sum of expression with scalar product in macro (#2178).
- Fixed writing of nonlinear models to MathOptFormat (#2181).
- Fixed construction of empty SparseAxisArray (#2179).
- Fixed constraint with zero function (#2188).
Version 0.21.1 (Feb 18, 2020)
- Improved the clarity of the
with_optimizer
deprecation warning.
Version 0.21.0 (Feb 16, 2020)
Breaking
Deprecated
with_optimizer
(#2090, #2084, #2141). You can replacewith_optimizer
by either nothing,optimizer_with_attributes
or a closure:- replace
with_optimizer(Ipopt.Optimizer)
byIpopt.Optimizer
. - replace
with_optimizer(Ipopt.Optimizer, max_cpu_time=60.0)
byoptimizer_with_attributes(Ipopt.Optimizer, "max_cpu_time" => 60.0)
. - replace
with_optimizer(Gurobi.Optimizer, env)
by() -> Gurobi.Optimizer(env)
. - replace
with_optimizer(Gurobi.Optimizer, env, Presolve=0)
byoptimizer_with_attributes(() -> Gurobi.Optimizer(env), "Presolve" => 0)
.
alternatively to
optimizer_with_attributes
, you can also set the attributes separately withset_optimizer_attribute
.- replace
Renamed
set_parameter
andset_parameters
toset_optimizer_attribute
andset_optimizer_attributes
(#2150).Broadcast should now be explicit inside macros.
@SDconstraint(model, x >= 1)
and@constraint(model, x + 1 in SecondOrderCone())
now throw an error instead of broadcasting1
along the dimension ofx
(#2107).@SDconstraint(model, x >= 0)
is now equivalent to@constraint(model, x in PSDCone())
instead of@constraint(model, (x .- 0) in PSDCone())
(#2107).The macros now create the containers with
map
instead offor
loops, as a consequence, containers created by@expression
can now have any element type and containers of constraint references now have concrete element types when possible. This fixes a long-standing issue where@expression
could only be used to generate a collection of linear expressions. Now it works for quadratic expressions as well (#2070).Calling
deepcopy(::AbstractModel)
now throws an error.The constraint name is now printed in the model string (#2108).
Added
- Added support for solver-independent and solver-specific callbacks (#2101).
- Added
write_to_file
andread_from_file
, supported formats are CBF, LP, MathOptFormat, MPS and SDPA (#2114). - Added support for complementarity constraints (#2132).
- Added support for indicator constraints (#2092).
- Added support for querying multiple solutions with the
result
keyword (#2100). - Added support for constraining variables on creation (#2128).
- Added method
delete
that deletes a vector of variables at once if it is supported by the underlying solver (#2135). - The arithmetic between JuMP expression has be refactored into the MutableArithmetics package (#2107).
- Improved error on complex values in NLP (#1978).
- Added an example of column generation (#2010).
Fixed
- Incorrect coefficients generated when using Symmetric variables (#2102)
Version 0.20.1 (Oct 18, 2019)
- Add sections on
@variables
and@constraints
in the documentation (#2062). - Fixed product of sparse matrices for Julia v1.3 (#2063).
- Added
set_objective_coefficient
to modify the coefficient of a linear term of the objective function (#2008). - Added
set_time_limit_sec
,unset_time_limit_sec
andtime_limit_sec
to set and query the time limit for the solver in seconds (#2053).
Version 0.20.0 (Aug 24, 2019)
- Documentation updates.
- Numerous bug fixes.
- Better error messages (#1977, #1978, #1997, #2017).
- Performance improvements (#1947, #2032).
- Added LP sensitivity summary functions
lp_objective_perturbation_range
andlp_rhs_perturbation_range
(#1917). - Added functions
dual_objective_value
,raw_status
andset_parameter
. - Added function
set_objective_coefficient
to modify the coefficient of a linear term of the objective (#2008). - Added functions
set_normalized_rhs
,normalized_rhs
, andadd_to_function_constant
to modify and get the constant part of a constraint (#1935, #1960). - Added functions
set_normalized_coefficient
andnormalized_coefficient
to modify and get the coefficient of a linear term of a constraint (#1935, #1960). - Numerous other improvements in MOI 0.9, see the
NEWS.md
file of MOI for more details.
Version 0.19.2 (June 8, 2019)
- Fix a bug in derivatives that could arise in models with nested nonlinear subexpressions.
Version 0.19.1 (May 12, 2019)
- Usability and performance improvements.
- Bug fixes.
Version 0.19.0 (February 15, 2019)
JuMP 0.19 contains significant breaking changes.
Breaking
JuMP's abstraction layer for communicating with solvers changed from MathProgBase (MPB) to MathOptInterface (MOI). MOI addresses many longstanding design issues. (See @mlubin's slides from JuMP-dev 2018.) JuMP 0.19 is compatible only with solvers that have been updated for MOI. See the installation guide for a list of solvers that have and have not yet been updated.
Most solvers have been renamed to
PackageName.Optimizer
. For example,GurobiSolver()
is nowGurobi.Optimizer
.Solvers are no longer added to a model via
Model(solver = XXX(kwargs...))
. Instead useModel(with_optimizer(XXX, kwargs...))
. For example,Model(with_optimizer(Gurobi.Optimizer, OutputFlag=0))
.JuMP containers (for example, the objects returned by
@variable
) have been redesigned.Containers.SparseAxisArray
replacesJuMPDict
,JuMPArray
was rewritten (inspired byAxisArrays
) and renamedContainers.DenseAxisArray
, and you can now request a container type with thecontainer=
keyword to the macros. See the corresponding documentation for more details.The statuses returned by solvers have changed. See the possible status values here. The MOI statuses are much richer than the MPB statuses and can be used to distinguish between previously indistinguishable cases (for example, did the solver have a feasible solution when it stopped because of the time limit?).
Starting values are separate from result values. Use
value
to query the value of a variable in a solution. Usestart_value
andset_start_value
to get and set an initial starting point provided to the solver. The solutions from previous solves are no longer automatically set as the starting points for the next solve.The data structures for affine and quadratic expressions
AffExpr
andQuadExpr
have changed. Internally, terms are stored in dictionaries instead of lists. Duplicate coefficients can no longer exist. Accessors and iteration methods have changed.JuMPNLPEvaluator
no longer includes the linear and quadratic parts of the model in the evaluation calls. These are now handled separately to allow NLP solvers that support various types of constraints.JuMP solver-independent callbacks have been replaced by solver-specific callbacks. See your favorite solver for more details. (See the note below: No solver-specific callbacks are implemented yet.)
The
norm()
syntax is no longer recognized inside macros. Use theSecondOrderCone()
set instead.JuMP no longer performs automatic transformation between special quadratic forms and second-order cone constraints. Support for these constraint classes depends on the solver.
The symbols
:Min
and:Max
are no longer used as optimization senses. Instead, JuMP uses theOptimizationSense
enum from MathOptInterface.@objective(model, Max, ...)
,@objective(model, Min, ...)
,@NLobjective(model, Max, ...)
, and@objective(model, Min, ...)
remain valid, but@objective(m, :Max, ...)
is no longer accepted.The sign conventions for duals has changed in some cases for consistency with conic duality (see the documentation). The
shadow_price
helper method returns duals with signs that match conventional LP interpretations of dual values as sensitivities of the objective value to relaxations of constraints.@constraintref
is no longer defined. Instead, create the appropriate container to hold constraint references manually. For example,constraints = Dict() # Optionally, specify types for improved performance. for i in 1:N constraints[i] = @constraint(model, ...) end
The
lowerbound
,upperbound
, andbasename
keyword arguments to the@variable
macro have been renamed tolower_bound
,upper_bound
, andbase_name
, for consistency with JuMP's new style recommendations.We rely on broadcasting syntax to apply accessors to collections of variables, for example,
value.(x)
instead ofgetvalue(x)
for collections. (Usevalue(x)
whenx
is a scalar object.)
Added
Splatting (like
f(x...)
) is recognized in restricted settings in nonlinear expressions.Support for deleting constraints and variables.
The documentation has been completely rewritten using docstrings and Documenter.
Support for modeling mixed conic and quadratic models (for example, conic models with quadratic objectives and bi-linear matrix inequalities).
Significantly improved support for modeling new types of constraints and for extending JuMP's macros.
Support for providing dual warm starts.
Improved support for accessing solver-specific attributes (for example, the irreducible inconsistent subsystem).
Explicit control of whether symmetry-enforcing constraints are added to PSD constraints.
Support for modeling exponential cones.
Significant improvements in internal code quality and testing.
Style and naming guidelines.
Direct mode and manual mode provide explicit control over when copies of a model are stored or regenerated. See the corresponding documentation.
Regressions
There are known regressions from JuMP 0.18 that will be addressed in a future release (0.19.x or later):
Performance regressions in model generation (issue). Please file an issue anyway if you notice a significant performance regression. We have plans to address a number of performance issues, but we might not be aware of all of them.
Fast incremental NLP solves are not yet reimplemented (issue).
We do not yet have an implementation of solver-specific callbacks.
The column generation syntax in
@variable
has been removed (that is, theobjective
,coefficients
, andinconstraints
keyword arguments). Support for column generation will be re-introduced in a future release.The ability to solve the continuous relaxation (that is, via
solve(model; relaxation = true)
) is not yet reimplemented (issue).
Version 0.18.5 (December 1, 2018)
- Support views in some derivative evaluation functions.
- Improved compatibility with PackageCompiler.
Version 0.18.4 (October 8, 2018)
- Fix a bug in model printing on Julia 0.7 and 1.0.
Version 0.18.3 (October 1, 2018)
- Add support for Julia v1.0 (Thanks @ExpandingMan)
- Fix matrix expressions with quadratic functions (#1508)
Version 0.18.2 (June 10, 2018)
- Fix a bug in second-order derivatives when expressions are present (#1319)
- Fix a bug in
@constraintref
(#1330)
Version 0.18.1 (April 9, 2018)
- Fix for nested tuple destructuring (#1193)
- Preserve internal model when relaxation=true (#1209)
- Minor bug fixes and updates for example
Version 0.18.0 (July 27, 2017)
- Drop support for Julia 0.5.
- Update for ForwardDiff 0.5.
- Minor bug fixes.
Version 0.17.1 (June 9, 2017)
- Use of
constructconstraint!
in@SDconstraint
. - Minor bug fixes.
Version 0.17.0 (May 27, 2017)
- Breaking change: Mixing quadratic and conic constraints is no longer supported.
- Breaking change: The
getvariable
andgetconstraint
functions are replaced by indexing on the corresponding symbol. For instance, to access the variable with namex
, one should now writem[:x]
instead ofgetvariable(m, :x)
. As a consequence, creating a variable and constraint with the same name now triggers a warning, and accessing one of them afterwards throws an error. This change is breaking only in the latter case. - Addition of the
getobjectivebound
function that mirrors the functionality of the MathProgBasegetobjbound
function except that it takes into account transformations performed by JuMP. - Minor bug fixes.
The following changes are primarily of interest to developers of JuMP extensions:
- The new syntax
@constraint(model, expr in Cone)
creates the constraint ensuring thatexpr
is insideCone
. TheCone
argument is passed toconstructconstraint!
which enables the call to the dispatched to an extension. - The
@variable
macro now callsconstructvariable!
instead of directly calling theVariable
constructor. Extra arguments and keyword arguments passed to@variable
are passed toconstructvariable!
which enables the call to be dispatched to an extension. - Refactor the internal function
conicdata
(used build the MathProgBase conic model) into smaller sub-functions to make these parts reusable by extensions.
Version 0.16.2 (March 28, 2017)
- Minor bug fixes and printing tweaks
- Address deprecation warnings for Julia 0.6
Version 0.16.1 (March 7, 2017)
- Better support for
AbstractArray
in JuMP (Thanks @tkoolen) - Minor bug fixes
Version 0.16.0 (February 23, 2017)
- Breaking change: JuMP no longer has a mechanism for selecting solvers by default (the previous mechanism was flawed and incompatible with Julia 0.6). Not specifying a solver before calling
solve()
will result in an error. - Breaking change: User-defined functions are no longer global. The first argument to
JuMP.register
is now a JuMPModel
object within whose scope the function will be registered. CallingJuMP.register
without aModel
now produces an error. - Breaking change: Use the new
JuMP.fix
method to fix a variable to a value or to update the value to which a variable is fixed. Callingsetvalue
on a fixed variable now results in an error in order to avoid silent behavior changes. (Thanks @joaquimg) - Nonlinear expressions now print out similarly to linear/quadratic expressions (useful for debugging!)
- New
category
keyword to@variable
. Used for specifying categories of anonymous variables. - Compatibility with Julia 0.6-dev.
- Minor fixes and improvements (Thanks @cossio, @ccoffrin, @blegat)
Version 0.15.1 (January 31, 2017)
- Bugfix for
@LinearConstraints
and friends
Version 0.15.0 (December 22, 2016)
- Julia 0.5.0 is the minimum required version for this release.
- Document support for BARON solver
- Enable info callbacks in more states than before, for example, for recording solutions. New
when
argument toaddinfocallback
(#814, thanks @yeesian) - Improved support for anonymous variables. This includes new warnings for potentially confusing use of the traditional non-anonymous syntax:
- When multiple variables in a model are given the same name
- When non-symbols are used as names, for example,
@variable(m, x[1][1:N])
- Improvements in iterating over JuMP containers (#836, thanks @IssamT)
- Support for writing variable names in .lp file output (Thanks @leethargo)
- Support for querying duals to SDP problems (Thanks @blegat)
- The comprehension syntax with curly braces
sum{}
,prod{}
, andnorm2{}
has been deprecated in favor of Julia's native comprehension syntaxsum()
,prod()
andnorm()
as previously announced. (For early adopters of the new syntax,norm2()
was renamed tonorm()
without deprecation.) - Unit tests rewritten to use Base.Test instead of FactCheck
- Improved support for operations with matrices of JuMP types (Thanks @ExpandingMan)
- The syntax to halt a solver from inside a callback has changed from
throw(CallbackAbort())
toreturn JuMP.StopTheSolver
- Minor bug fixes
Version 0.14.2 (December 12, 2016)
- Allow singleton anonymous variables (includes bugfix)
Version 0.14.1 (September 12, 2016)
- More consistent handling of states in informational callbacks, includes a new
when
parameter toaddinfocallback
for specifying in which state an informational callback should be called.
Version 0.14.0 (August 7, 2016)
- Compatibility with Julia 0.5 and ForwardDiff 0.2
- Support for "anonymous" variables, constraints, expressions, and parameters, for example,
x = @variable(m, [1:N])
instead of@variable(m, x[1:N])
- Support for retrieving constraints from a model by name via
getconstraint
@NLconstraint
now returns constraint references (as expected).- Support for vectorized expressions within lazy constraints
- On Julia 0.5, parse new comprehension syntax
sum(x[i] for i in 1:N if isodd(i))
instead ofsum{ x[i], i in 1:N; isodd(i) }
. The old syntax with curly braces will be deprecated in JuMP 0.15. - Now possible to provide nonlinear expressions as "raw" Julia
Expr
objects instead of using JuMP's nonlinear macros. This input format is useful for programmatically generated expressions. s/Mathematical Programming/Mathematical Optimization/
- Support for local cuts (Thanks to @madanim, Mehdi Madani)
- Document Xpress interface developed by @joaquimg, Joaquim Dias Garcia
- Minor bug and deprecation fixes (Thanks @odow, @jrevels)
Version 0.13.2 (May 16, 2016)
- Compatibility update for MathProgBase
Version 0.13.1 (May 3, 2016)
- Fix broken deprecation for
registerNLfunction
.
Version 0.13.0 (April 29, 2016)
- Most exported methods and macros have been renamed to avoid camelCase. See the list of changes here. There is a 1-1 mapping from the old names to the new, and it is safe to simply replace the names to update existing models.
- Specify variable lower/upper bounds in
@variable
using thelowerbound
andupperbound
keyword arguments. - Change name printed for variable using the
basename
keyword argument to@variable
. - New
@variables
macro allows multi-line declaration of groups of variables. - A number of solver methods previously available only through MathProgBase are now exposed directly in JuMP. The fix was recorded live.
- Compatibility fixes with Julia 0.5.
- The "end" indexing syntax is no longer supported within JuMPArrays which do not use 1-based indexing until upstream issues are resolved, see here.
Version 0.12.2 (March 9, 2016)
- Small fixes for nonlinear optimization
Version 0.12.1 (March 1, 2016)
- Fix a regression in slicing for JuMPArrays (when not using 1-based indexing)
Version 0.12.0 (February 27, 2016)
- The automatic differentiation functionality has been completely rewritten with a number of user-facing changes:
@defExpr
and@defNLExpr
now take the model as the first argument. The previous one-argument version of@defExpr
is deprecated; all expressions should be named. For example, replace@defExpr(2x+y)
with@defExpr(jump_model, my_expr, 2x+y)
.- JuMP no longer uses Julia's variable binding rules for efficiently re-solving a sequence of nonlinear models. Instead, we have introduced nonlinear parameters. This is a breaking change, so we have added a warning message when we detect models that may depend on the old behavior.
- Support for user-defined functions integrated within nonlinear JuMP expressions.
- Replaced iteration over
AffExpr
withNumber
-like scalar iteration; previous iteration behavior is now available vialinearterms(::AffExpr)
. - Stopping the solver via
throw(CallbackAbort())
from a callback no longer triggers an exception. Instead,solve()
returnsUserLimit
status. getDual()
now works for conic problems (Thanks @emreyamangil.)
Version 0.11.3 (February 4, 2016)
- Bug-fix for problems with quadratic objectives and semidefinite constraints
Version 0.11.2 (January 14, 2016)
- Compatibility update for Mosek
Version 0.11.1 (December 1, 2015)
- Remove usage of
@compat
in tests. - Fix updating quadratic objectives for nonlinear models.
Version 0.11.0 (November 30, 2015)
- Julia 0.4.0 is the minimum required version for this release.
- Fix for scoping semantics of index variables in sum{}. Index variables no longer leak into the surrounding scope.
- Addition of the
solve(m::Model, relaxation=true)
keyword argument to solve the standard continuous relaxation of modelm
- The
getConstraintBounds()
method allows access to the lower and upper bounds of all constraints in a (nonlinear) model. - Update for breaking changes in MathProgBase
Version 0.10.3 (November 20, 2015)
- Fix a rare error when parsing quadratic expressions
- Fix
Variable()
constructor with default arguments - Detect unrecognized keywords in
solve()
Version 0.10.2 (September 28, 2015)
- Fix for deprecation warnings
Version 0.10.1 (September 3, 2015)
- Fixes for ambiguity warnings.
- Fix for breaking change in precompilation syntax in Julia 0.4-pre
Version 0.10.0 (August 31, 2015)
- Support (on Julia 0.4 and later) for conditions in indexing
@defVar
and@addConstraint
constructs, for example,@defVar(m, x[i=1:5,j=1:5; i+j >= 3])
- Support for vectorized operations on Variables and expressions. See the documentation for details.
- New
getVar()
method to access variables in a model by name - Support for semidefinite programming.
- Dual solutions are now available for general nonlinear problems. You may call
getDual
on a reference object for a nonlinear constraint, andgetDual
on a variable object for Lagrange multipliers from active bounds. - Introduce warnings for two common performance traps: too many calls to
getValue()
on a collection of variables and use of the+
operator in a loop to sum expressions. - Second-order cone constraints can be written directly with the
norm()
andnorm2{}
syntax. - Implement MathProgBase interface for querying Hessian-vector products.
- Iteration over
JuMPContainer
s is deprecated; instead, use thekeys
andvalues
functions, andzip(keys(d),values(d))
for the old behavior. @defVar
returnsArray{Variable,N}
when each ofN
index sets are of the form1:nᵢ
.- Module precompilation: on Julia 0.4 and later,
using JuMP
is now much faster.
Version 0.9.3 (August 11, 2015)
- Fixes for FactCheck testing on julia v0.4.
Version 0.9.2 (June 27, 2015)
- Fix bug in @addConstraints.
Version 0.9.1 (April 25, 2015)
- Fix for Julia 0.4-dev.
- Small infrastructure improvements for extensions.
Version 0.9.0 (April 18, 2015)
- Comparison operators for constructing constraints (for example,
2x >= 1
) have been deprecated. Instead, construct the constraints explicitly in the@addConstraint
macro to add them to the model, or in the@LinearConstraint
macro to create a stand-alone linear constraint instance. getValue()
method implemented to compute the value of a nonlinear subexpression- JuMP is now released under the Mozilla Public License version 2.0 (was previously LGPL). MPL is a copyleft license which is less restrictive than LGPL, especially for embedding JuMP within other applications.
- A number of performance improvements in ReverseDiffSparse for computing derivatives.
MathProgBase.getsolvetime(m)
now returns the solution time reported by the solver, if available. (Thanks @odow, Oscar Dowson)- Formatting fix for LP format output. (Thanks @sbebo, Leonardo Taccari).
Version 0.8.0 (February 17, 2015)
- Nonlinear subexpressions now supported with the
@defNLExpr
macro. - SCS supported for solving second-order conic problems.
setXXXCallback
family deprecated in favor ofaddXXXCallback
.- Multiple callbacks of the same type can be registered.
- Added support for informational callbacks via
addInfoCallback
. - A
CallbackAbort
exception can be thrown from callback to safely exit optimization.
Version 0.7.4 (February 4, 2015)
- Reduced costs and linear constraint duals are now accessible when quadratic constraints are present.
- Two-sided nonlinear constraints are supported.
- Methods for accessing the number of variables and constraints in a model are renamed.
- New default procedure for setting initial values in nonlinear optimization: project zero onto the variable bounds.
- Small bug fixes.
Version 0.7.3 (January 14, 2015)
- Fix a method ambiguity conflict with Compose.jl (cosmetic fix)
Version 0.7.2 (January 9, 2015)
- Fix a bug in
sum(::JuMPDict)
- Added the
setCategory
function to change a variables category (for example, continuous or binary)
after construction, and getCategory
to retrieve the variable category.
Version 0.7.1 (January 2, 2015)
- Fix a bug in parsing linear expressions in macros. Affects only Julia 0.4 and later.
Version 0.7.0 (December 29, 2014)
Linear/quadratic/conic programming
- Breaking change: The syntax for column-wise model generation has been changed to use keyword arguments in
@defVar
. - On Julia 0.4 and later, variables and coefficients may be multiplied in any order within macros. That is, variable*coefficient is now valid syntax.
- ECOS supported for solving second-order conic problems.
Nonlinear programming
- Support for skipping model generation when solving a sequence of nonlinear models with changing data.
- Fix a memory leak when solving a sequence of nonlinear models.
- The
@addNLConstraint
macro now supports the three-argument version to define sets of nonlinear constraints. - KNITRO supported as a nonlinear solver.
- Speed improvements for model generation.
- The
@addNLConstraints
macro supports adding multiple (groups of) constraints at once. Syntax is similar to@addConstraints
. - Discrete variables allowed in nonlinear problems for solvers which support them (currently only KNITRO).
General
- Starting values for variables may now be specified with
@defVar(m, x, start=value)
. - The
setSolver
function allows users to change the solver subsequent to model creation. - Support for "fixed" variables via the
@defVar(m, x == 1)
syntax. - Unit tests rewritten to use FactCheck.jl, improved testing across solvers.
Version 0.6.3 (October 19, 2014)
- Fix a bug in multiplying two AffExpr objects.
Version 0.6.2 (October 11, 2014)
- Further improvements and bug fixes for printing.
- Fixed a bug in
@defExpr
. - Support for accessing expression graphs through the MathProgBase NLP interface.
Version 0.6.1 (September 19, 2014)
- Improvements and bug fixes for printing.
Version 0.6.0 (September 9, 2014)
- Julia 0.3.0 is the minimum required version for this release.
buildInternalModel(m::Model)
added to build solver-level model in memory without optimizing.- Deprecate
load_model_only
keyword argument tosolve
. - Add groups of constraints with
@addConstraints
macro. - Unicode operators now supported, including
∑
forsum
,∏
forprod
, and≤
/≥
- Quadratic constraints supported in
@addConstraint
macro. - Quadratic objectives supported in
@setObjective
macro. - MathProgBase solver-independent interface replaces Ipopt-specific interface for nonlinear problems
- Breaking change:
IpoptOptions
no longer supported to specify solver options, usem = Model(solver=IpoptSolver(options...))
instead.
- Breaking change:
- New solver interfaces: ECOS, NLopt, and nonlinear support for MOSEK
- New option to control whether the lazy constraint callback is executed at each node in the B&B tree or just when feasible solutions are found
- Add support for semicontinuous and semi-integer variables for those solvers that support them.
- Add support for index dependencies (for example, triangular indexing) in
@defVar
,@addConstraint
, and@defExpr
(for example,@defVar(m, x[i=1:10,j=i:10])
).- This required some changes to the internal structure of JuMP containers, which may break code that explicitly stored
JuMPDict
objects.
- This required some changes to the internal structure of JuMP containers, which may break code that explicitly stored
Version 0.5.8 (September 24, 2014)
- Fix a bug with specifying solvers (affects Julia 0.2 only)
Version 0.5.7 (September 5, 2014)
- Fix a bug in printing models
Version 0.5.6 (September 2, 2014)
- Add support for semicontinuous and semi-integer variables for those solvers that support them.
- Breaking change: Syntax for
Variable()
constructor has changed (use of this interface remains discouraged)
- Breaking change: Syntax for
- Update for breaking changes in MathProgBase
Version 0.5.5 (July 6, 2014)
- Fix bug with problem modification: adding variables that did not appear in existing constraints or objective.
Version 0.5.4 (June 19, 2014)
- Update for breaking change in MathProgBase which reduces loading times for
using JuMP
- Fix error when MIPs not solved to optimality
Version 0.5.3 (May 21, 2014)
- Update for breaking change in ReverseDiffSparse
Version 0.5.2 (May 9, 2014)
- Fix compatibility with Julia 0.3 prerelease
Version 0.5.1 (May 5, 2014)
- Fix a bug in coefficient handling inside lazy constraints and user cuts
Version 0.5.0 (May 2, 2014)
- Support for nonlinear optimization with exact, sparse second-order derivatives automatically computed. Ipopt is currently the only solver supported.
getValue
forAffExpr
andQuadExpr
- Breaking change:
getSolverModel
replaced bygetInternalModel
, which returns the internal MathProgBase-level model - Groups of constraints can be specified with
@addConstraint
(see documentation for details). This is not a breaking change. dot(::JuMPDict{Variable},::JuMPDict{Variable})
now returns the corresponding quadratic expression.
Version 0.4.1 (March 24, 2014)
- Fix bug where change in objective sense was ignored when re-solving a model.
- Fix issue with handling zero coefficients in AffExpr.
Version 0.4.0 (March 10, 2014)
- Support for SOS1 and SOS2 constraints.
- Solver-independent callback for user heuristics.
dot
andsum
implemented forJuMPDict
objects. Now you can say@addConstraint(m, dot(a,x) <= b)
.- Developers: support for extensions to JuMP. See definition of Model in
src/JuMP.jl
for more details. - Option to construct the low-level model before optimizing.
Version 0.3.2 (February 17, 2014)
- Improved model printing
- Preliminary support for IJulia output
Version 0.3.1 (January 30, 2014)
- Documentation updates
- Support for MOSEK
- CPLEXLink renamed to CPLEX
Version 0.3.0 (January 21, 2014)
- Unbounded/infeasibility rays:
getValue()
will return the corresponding components of an unbounded ray when a model is unbounded, if supported by the selected solver.getDual()
will return an infeasibility ray (Farkas proof) if a model is infeasible and the selected solver supports this feature. - Solver-independent callbacks for user generated cuts.
- Use new interface for solver-independent QCQP.
setlazycallback
renamed tosetLazyCallback
for consistency.
Version 0.2.0 (December 15, 2013)
Breaking
- Objective sense is specified in
setObjective
instead of in theModel
constructor. lpsolver
andmipsolver
merged into singlesolver
option.
Added
- Problem modification with efficient LP restarts and MIP warm-starts.
- Relatedly, column-wise modeling now supported.
- Solver-independent callbacks supported. Currently we support only a "lazy constraint" callback, which works with Gurobi, CPLEX, and GLPK. More callbacks coming soon.
Version 0.1.2 (November 16, 2013)
- Bug fixes for printing, improved error messages.
- Allow
AffExpr
to be used in macros; for example,ex = y + z; @addConstraint(m, x + 2*ex <= 3)
Version 0.1.1 (October 23, 2013)
- Update for solver specification API changes in MathProgBase.
Version 0.1.0 (October 3, 2013)
- Initial public release.