A hybrid crow search algorithm to minimise the weighted sum of makespan and total flow time in a flow shop environment

M. K. Marichelvam, M. Geetha
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引用次数: 3

Abstract

In this paper, flow shop scheduling problems which were proved to be strongly NP-hard (non-deterministic polynomial time hard) are considered. The objective is to minimise the weighted sum of makespan and total flow time. For solving this problem, a recently developed meta-heuristics algorithm called as crow search algorithm is proposed. Moreover, the dispatching rules are hybridised with the crow search algorithm to improve the solution quality. An evaluation of the performance of the proposed algorithm is carried out by industrial scheduling problem and the results are compared with many dispatching rules and constructive heuristics. The results obtained by the proposed algorithm are much better than the dispatching rules and constructive heuristics. Random problem instances are also used to validate the performance of the proposed algorithm. The results are compared with many other meta-heuristics addressed in the literature and the results indicate the effectiveness of the proposed algorithm in terms of solution quality and computational time. To the best of our knowledge this is the first reported application of crow search algorithm to solve the scheduling problems.
流动车间环境下最大完工时间和总流程时间加权最小的混合乌鸦搜索算法
本文研究了被证明具有强np困难(非确定性多项式时间困难)的流水车间调度问题。目标是最小化完工时间和总流程时间的加权总和。为了解决这一问题,提出了一种新的元启发式算法——乌鸦搜索算法。并将调度规则与乌鸦搜索算法相结合,提高了求解质量。通过工业调度问题对所提算法的性能进行了评价,并与许多调度规则和建设性启发式方法进行了比较。该算法得到的结果比调度规则和建设性启发式算法要好得多。随机问题实例也用于验证所提算法的性能。结果与文献中讨论的许多其他元启发式方法进行了比较,结果表明所提出的算法在解决质量和计算时间方面是有效的。据我们所知,这是第一个应用乌鸦搜索算法解决调度问题的报道。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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