Audience: Computer Scientists, Mathematicians, Operations Researchers

Aims and Scope: Mathematical Programming Computation (MPC) publishes original research articles covering computational issues in mathematical optimization. Articles report on innovative software, comparative tests, modeling environments, libraries of data, and/or applications. A main feature of the journal is the inclusion of accompanying software and data with submitted manuscripts. The journal’s review process includes the evaluation and testing of the accompanying software. Where possible, the review will aim for verification of reported computational results.

Topics covered in MPC include linear programming, convex optimization, nonlinear optimization, stochastic optimization, robust optimization, integer programming, combinatorial optimization, global optimization, network algorithms, and modeling languages.

MPC supports the creation and distribution of open-source software. Submitted software is archived with the corresponding research articles. The software is not updated and the journal is not intended to be the point of distribution for the software. The author’s licensing information is included with the archived software. Articles describing non-open software are also considered for publication, provided reviewers are given access to executable codes that can be used to evaluate reported computational results.

Link to the Mathematical Programming Computation home page.

Editorial Board

All information on the editorial board of Mathematical Programming Computation can be found here.