MPC - Mathematical Programming Computation

Mathematical Programming Computation

A journal of the Mathematical Optimization Society and Springer Verlag
Volume: 2020

Editor-in-Chief: Jonathan Eckstein, Rutgers University

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.

Best Paper Award in 2019

The Editorial Board voted to share that award between these two papers:

A computational comparison of symmetry handling methods for mixed integer programs
Marc Pfetsch, Thomas Rehn
Full Text: PDF
A derivative-free Gauss–Newton method
Coralia Cartis, Lindon Roberts
Full Text: PDF

Current Issue

Volume 12, Issue 3, September 2020

Robust Euclidean embedding via EDM optimization

Shenglong Zhou, Naihua Xiu, Hou-Duo Qi

PDF

Generation techniques for linear programming instances with controllable properties

Simon Bowly, Kate Smith-Miles, Davaatseren Baatar, Hans Mittelmann

PDF

A rotation-based branch-and-price approach for the nurse scheduling problem

Antoine Legrain, Jérémy Omer, Samuel Rosat

PDF

An adaptive primal-dual framework for nonsmooth convex minimization

Quoc Tran-Dinh, Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher

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Parsimonious formulations for low-diameter clusters

Hosseinali Salemi, Austin Buchanan

PDF

Call for Papers

Mathematical Programming Computation (MPC) is a new journal of the Mathematical Programming Society. The field of mathematical programming concerns the minimization and maximization of real-valued functions, subject to constraints on the variables. MPC publishes original research articles covering computational issues surrounding these problems, including reports on innovative software, comparative tests, modeling environments, libraries of data, and applications.

A main feature of MPC 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.

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. Authors are highly encouraged to provide the source code of their software. Submitted software is archived with the corresponding research articles. T he 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.

Aims and Scope

Mathematical Programming Computation (MPC) publishes original research articles advancing the state of the art of practical computation in Mathematical Optimization and closely related fields. Authors are required to submit software source code and data along with their manuscripts (while open-source software is encouraged, it is not required). Where applicable, the review process will aim for verification of reported computational results.

Topics of articles include:

New algorithmic techniques, with substantial computational testing
New applications, with substantial computational testing
Innovative software
Comparative tests of algorithms
Modeling environments
Libraries of problem instances
Software frameworks or libraries.

Among the specific topics covered in MPC are linear programming, convex optimization, nonlinear optimization, stochastic optimization, integer programming, combinatorial optimization, global optimization, network algorithms, and modeling languages.

Manuscript Submission

Authors are invited to submit articles for possible publication in MPC. Research articles can be submitted in Adobe PDF format through the MPC Submission Web Site.

Journal Distribution

MPC is published by Springer Verlag, with the first volume, consisting of four issues, appearing in 2009. All members of the Mathematical Programming Society receive print versions of the journal as part of their membership benefits. The contents of the journal will be made available on the society-run MPC web site, open to members and nonmembers. Supplementary material will be included on the web site, supporting the computational studies described in the journal articles.