Heuristics and metaheuristics to minimize makespan for flowshop with peak power consumption constraints

IF 1.6 3区 工程技术 Q4 ENGINEERING, INDUSTRIAL
Yuan-Zhen Li, K. Gao, Lei-lei Meng, Xue-Lei Jing, Biao Zhang
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引用次数: 2

Abstract

This paper addresses the permutation flowshop scheduling problem with peak power consumption constraints (PFSPP). The real-time power consumption of the PFSPP cannot exceed a given peak power at any time. First, a mathematical model is established to describe the concerned problem. The sequence of operations is taken as a solution and the characteristics of solutions are analyzed. Based on the problem characteristics, eight heuristics are proposed, including balanced machine-job decoding method, balanced machine-job insert method, balanced job-machine insert method, balanced machine-job group insert method, balanced job-machine group insert method, greedy algorithm, beam search algorithm, and improved beam search algorithm. Similarly, the canonical artificial bee colony algorithm and iterated local search algorithm are modified based on the problem characteristics to solve the PFSPP. A large number of experiments are carried out to evaluate the performance of new proposed heuristics and metaheuristics. The results and discussion show that the proposed heuristics and metaheuristics perform well in solving the PFSPP.
带峰值功耗约束的流程车间最大完工时间最小化的启发式和元启发式方法
研究了带峰值功耗约束的置换流水车间调度问题。PFSPP的实时功耗在任何时候都不能超过给定的峰值功率。首先,建立数学模型来描述所关注的问题。将操作序列作为一个解,并分析了解的特性。根据问题特点,提出了8种启发式算法,包括平衡机器作业译码法、平衡机器作业插入法、平衡作业-机器插入法、平衡机器作业组插入法、平衡作业-机器组插入法、贪婪算法、波束搜索算法和改进波束搜索算法。同样,根据问题的特点,改进了规范人工蜂群算法和迭代局部搜索算法来求解PFSPP问题。为了评估新提出的启发式和元启发式的性能,进行了大量的实验。结果和讨论表明,所提出的启发式方法和元启发式方法在求解PFSPP问题上表现良好。
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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来源期刊
CiteScore
5.70
自引率
9.10%
发文量
35
审稿时长
20 weeks
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