Multi-objective Scheduling Optimization in Job Shop with Unrelated Parallel Machines Using NSGA-III

被引:0
作者
dos Santos, Francisco [1 ,2 ]
Costa, Lino [1 ,3 ]
Varela, Leonilde [1 ,3 ]
机构
[1] Univ Minho, ALGORITMI Res Ctr LASI, Braga, Portugal
[2] Kimpa Vita Univ, Polytech Inst, Uige, Angola
[3] Univ Minho, Dept Prod & Syst, Braga, Portugal
来源
COMPUTATIONAL SCIENCE AND ITS APPLICATIONS-ICCSA 2024 WORKSHOPS, PT II | 2024年 / 14816卷
关键词
Job shop scheduling problem; multi-objective optimization; evolutionary algorithms; ALGORITHM; MAKESPAN; MINIMIZE;
D O I
10.1007/978-3-031-65223-3_25
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Job shop scheduling problems are common in the engineering field. In spite of some approaches consider just the most important objective to optimize, several other conflicting criteria are also important. Multi-objective optimization algorithms can be used to solve these problems optimizing, simultaneously, two or more objectives. However, when the number of objectives increases, the problems become more challenging. This paper presents the results of the optimization of a set of job shop scheduling with unrelated parallel machines and sequence-dependent setup times, using the NSGA-III. Several instances with different sizes in terms of number of jobs and machines are considered. The goal is to assign jobs to machines in order to simultaneously minimize the maximum job completion time (makespan), the average job completion time and the standard deviation of the job completion time. These results are analysed and confirm the validity and highlight the advantages of this approach.
引用
收藏
页码:370 / 382
页数:13
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