An active set algorithm for robust combinatorial optimization based on separation oracles

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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.

数学规划计算（MPC）发表原创研究文章，推进数学优化和密切相关领域的实际计算的技术水平。作者必须提交软件源代码和数据沿着他们的手稿（虽然鼓励使用开源软件，但并不要求）。在适用情况下，审查过程旨在验证报告的计算结果。文章的主题包括：新的算法技术，大量的计算测试新的应用程序，大量的计算测试创新软件算法的比较测试建模环境问题实例库软件框架或库。MPC涵盖的具体主题包括线性规划，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。MPC接受自己的编辑委员会成员提交的稿件，前提是处理稿件的副编辑、审稿人和技术编辑的身份可以完全保密。编辑委员会成员提交的稿件必须达到与所有其他被接受稿件相同的质量标准，才能被接受;这些意见书绝对不会获得特别优待或考虑。

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