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An In-Out Approach to Disjunctive Optimization

机译:析出优化的一种由内而外的方法

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摘要

Cutting plane methods are widely used for solving convex optimization problems and are of fundamental importance, e.g., to provide tight bounds for Mixed-Integer Programs (MIPs). This is obtained by embedding a cut-separation module within a search scheme. The importance of a sound search scheme is well known in the Constraint Programming (CP) community. Unfortunately, the "standard" search scheme typically used for MIP problems, known as the Kelley method, is often quite unsatisfactory because of saturation issues. In this paper we address the so-called Lift-and-Project closure for 0-1 MIPs associated with all disjunctive cuts generated from a given set of elementary disjunction. We focus on the search scheme embedding the generated cuts. In particular, we analyze a general meta-scheme for cutting plane algorithms, called in-out search, that was recently proposed by Ben-Ameur and Neto [1]. Computational results on test instances from the literature are presented, showing that using a more clever meta-scheme on top of a black-box cut generator may lead to a significant improvement.
机译:剖切面方法广泛用于解决凸优化问题,并且具有根本的重要性,例如为混合整数程序(MIP)提供紧密边界。这是通过在搜索方案中嵌入剪切分离模块而获得的。声音搜索方案的重要性在约束编程(CP)社区中众所周知。不幸的是,由于饱和度问题,通常用于MIP问题的“标准”搜索方案(称为Kelley方法)通常不能令人满意。在本文中,我们针对0-1 MIP的所谓的“提升和项目”闭合与从给定的基本析取集生成的所有析取切割相关。我们专注于嵌入生成的切割的搜索方案。特别是,我们分析了Ben-Ameur和Neto [1]最近提出的用于切面算法的通用元方案,称为进出搜索。给出了来自文献的测试实例的计算结果,表明在黑盒切割生成器顶部使用更聪明的元方案可能会带来显着的改进。

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