Mathematical Programming Computation
Mathematical Programming Computation: Aims and Scope
Mathematical Programming Computation (MPC) publishes original research articles covering computational issues in mathematical programming. 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 software and data that foster further computational research. The opinion of the reviewers concerning this aspect of the provided material is a considerable factor in the editorial decision process. Another factor is the extent to which the reviewers are able to verify the reported computational results. To these aims, authors are highly encouraged to provide the source code of their 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. In case the software is no longer available through other means, MPC will distribute it on individual request under the license given by the author. The intent is to at least partly remedy today's situation where it is often impossible to compare new results with those computed by other codes several years ago.
Articles describing software where no source code is made available are acceptable, provided reviewers are given access to executable codes that can be used to evaluate reported computational results. Articles may also provide data, their description, and analysis. Articles not providing any software or data will also be considered, provided they advance the state-of-the-art regarding a computational topic.