Mathematical Programming Computation

期刊简介：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.MPC accepts manuscript submission from its own editorial board members in cases in which the identities of the associate editor, reviewers, and technical editor handling the manuscript can remain fully confidential. To be accepted, manuscripts submitted by editorial board members must meet the same quality standards as all other accepted submissions; there is absolutely no special preference or consideration given to such submissions.

【译文】《数学规划计算》（MPC）发表原创研究文章，推动数学优化及其相关领域实用计算的前沿发展。作者需随稿件提交软件源代码和数据（虽然鼓励开源软件，但不是必需的）。在适用的情况下，审稿过程将致力于验证报告的计算结果。文章主题包括：具有大量计算测试的新算法技术、具有大量计算测试的新应用、创新软件、算法比较测试、建模环境、问题实例库、软件框架或库。MPC在其特定主题中包括线性规划、凸优化、非线性优化、随机优化、整数规划、组合优化、全局优化、网络算法和建模语言。在关联编辑、审稿人和处理该稿件的编辑技术人员的身份可以完全保密的情况下，MPC接受其编委会成员的稿件提交。编委会成员提交的稿件必须符合所有其他接受提交的质量标准；此类提交绝对没有特殊偏好或考虑。