本德分解
分解
整数规划
数学优化
计算机科学
约束规划
对偶(语法数字)
分解法(排队论)
对偶(序理论)
过程(计算)
理论计算机科学
算法
数学
程序设计语言
离散数学
艺术
生态学
文学类
随机规划
生物
作者
T. Davies,Graeme Gange,Peter J. Stuckey
出处
期刊:Proceedings of the ... AAAI Conference on Artificial Intelligence
[Association for the Advancement of Artificial Intelligence (AAAI)]
日期:2017-02-12
卷期号:31 (1)
被引量:9
标识
DOI:10.1609/aaai.v31i1.10654
摘要
Logic-based Benders decomposition (LBBD) is a powerful hybrid optimisation technique that can combine the strong dual bounds of mixed integer programming (MIP) with the combinatorial search strengths of constraint programming (CP). A major drawback of LBBD is that it is a far more involved process to implement an LBBD solution to a problem than the "model-and-run" approach provided by both CP and MIP. We propose an automated approach that accepts an arbitrary MiniZinc model and solves it using LBBD with no additional intervention on the part of the modeller. The design of this approach also reveals an interesting duality between LBBD and large neighborhood search (LNS). We compare our implementation of this approach to CP and MIP solvers on 4 different problem classes where LBBD has been applied before.
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