IDENTICAL PARALLEL MACHINES SCHEDULING USING GENETIC ALGORITHM

A. J. Haleel
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引用次数: 0

Abstract

Minimizing the scheduling production time consider one of the most important factors forcompanies which their objectives is achieve the maximum profits. This paper studies theidentical parallel machine scheduling problem which involves the assignment numbers ofjob (N) to set of identical parallel machine (M) in order to minimize the makespan(maximum completion time of all job). There are numerous troubles in solving the largesize of “parallel machine scheduling” problem with an excessive jobs and machines, sothe genetic algorithm was proposed in this paper which is consider an efficient algorithmthat fits larger size of identical “parallel machine scheduling” for minimizing themakespan. Most studies in the scheduling field suppose setup time is insignificant orincluded in the processing time, in this paper both the sequence independent setup timesand processing time were considered. The solutions of algorithms are coding in(MATLAB). A numerical example of (11) jobs are schedule on (3) machines todemonstrative the effectiveness of algorithm solution. The result show the algorithm caneffectively solve large size of scheduling problem and given the best schedule withminimum makespan.
基于遗传算法的相同并行机调度
最小化生产调度时间是企业实现利润最大化的重要因素之一。研究了以最大完工时间(makespan)为目标,将若干个作业分配给一组相同的并行机(M)的同行机调度问题。在解决作业和机器数量过多的大规模“并行机器调度”问题时存在诸多困难,因此本文提出了遗传算法,认为遗传算法是一种有效的算法,可以适应规模较大的相同“并行机器调度”,以最小化完工时间。大多数调度领域的研究都假设装配时间不重要或包含在加工时间中,本文同时考虑了与序列无关的装配时间和加工时间。算法的解在MATLAB中进行了编码。以(11)个作业在(3)台机器上调度为例,验证了算法的有效性。结果表明,该算法能有效地解决大规模调度问题,并给出最大完工时间最小的最佳调度方案。
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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24 weeks
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