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Introduction

Welcome to the documentation for MathOptInterface.

Note

This documentation is also available in PDF format: MathOptInterface.pdf.

What is MathOptInterface?

MathOptInterface.jl (MOI) is an abstraction layer designed to provide a unified interface to mathematical optimization solvers so that users do not need to understand multiple solver-specific APIs.

Tip

This documentation is aimed at developers writing software interfaces to solvers and modeling languages using the MathOptInterface API. If you are a user interested in solving optimization problems, we encourage you instead to use MOI through a higher-level modeling interface like JuMP or Convex.jl.

How the documentation is structured

Having a high-level overview of how this documentation is structured will help you know where to look for certain things.

  • The Tutorials section contains articles on how to use and implement the MathOptInteraface API. Look here if you want to write a model in MOI, or write an interface to a new solver.
  • The Manual contains short code-snippets that explain how to use the MOI API. Look here for more details on particular areas of MOI.
  • The Background section contains articles on the theory behind MathOptInterface. Look here if you want to understand why, rather than how.
  • The API Reference contains a complete list of functions and types that comprise the MOI API. Look here if you want to know how to use (or implement) a particular function.
  • The Submodules section contains stand-alone documentation for each of the submodules within MOI. These submodules are not required to interface a solver with MOI, but they make the job much easier.

Citing MathOptInterface

If you find MathOptInterface useful in your work, we kindly request that you cite the following paper:

@article{legat2021mathoptinterface,
    title={{MathOptInterface}: a data structure for mathematical optimization problems},
    author={Legat, Beno{\^\i}t and Dowson, Oscar and Garcia, Joaquim Dias and Lubin, Miles},
    journal={INFORMS Journal on Computing},
    year={2021},
    doi={10.1287/ijoc.2021.1067},
    publisher={INFORMS}
}

A preprint of this paper is freely available.