Comparisons of metaheuristic algorithms for unrelated parallel machine weighted earliness/tardiness scheduling problems

被引：0
作者：
Oğuzhan Ahmet Arık
机构：
[1] Nuh Naci Yazgan University,Industrial Engineering Department
来源：
Evolutionary Intelligence | 2020年 / 13卷
关键词：
Artificial bee colony; Genetic algorithm; Simulated annealing; Earliness/tardiness; Parallel machine; Scheduling;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper investigates unrelated parallel machine scheduling problems where the objectives are to minimize total weighted sum of earliness/tardiness costs. Three different metaheuristic algorithms are compared with others to determine what kind (swarm intelligence based, evolutionary or single solution) of metaheuristics is effective to solve these problems. In this study, artificial bee colony (ABC), genetic algorithm and simulated annealing algorithm are chosen as swarm intelligence based algorithm, evolutionary algorithm and single solution algorithm. All proposed algorithms are created without modification in order to determine effectiveness of these metaheuristics. Experimental results show that ABC outperforms its opponents in view of solution quality as swarm intelligence based metaheuristic algorithm.
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页码：415 / 425
页数：10
相关论文
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