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Iterative beam search algorithms for the permutation flowshop
arXiv - CS - Neural and Evolutionary Computing Pub Date : 2020-09-12 , DOI: arxiv-2009.05800
Luc Libralesso, Pablo Andres Focke, Aur\'elien Secardin, Vincent Jost

We study an iterative beam search algorithm for the permutation flowshop (makespan and flowtime minimization). This algorithm combines branching strategies inspired by recent branch-and-bounds and a guidance strategy inspired by the LR heuristic. It obtains competitive results, reports many new-best-so-far solutions on the VFR benchmark (makespan minimization) and the Taillard benchmark (flowtime minimization) without using any NEH-based branching or iterative-greedy strategy. The source code is available at: https://gitlab.com/librallu/cats-pfsp.

中文翻译:

置换流水车间的迭代波束搜索算法

我们研究了置换流水车间的迭代波束搜索算法(makespan 和 flowtime 最小化)。该算法结合了受最近分支定界启发的分支策略和受 LR 启发式启发的指导策略。它获得了有竞争力的结果,在 VFR 基准(最小化)和 Taillard 基准(流时间最小化)上报告了许多新的迄今为止最好的解决方案,而没有使用任何基于 NEH 的分支或迭代贪婪策略。源代码位于:https://gitlab.com/librallu/cats-pfsp。
更新日期:2020-09-15
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