A genetic algorithm for the hybrid flow shop scheduling with unrelated machines and machine eligibility

被引：100
|
作者：
Yu, Chunlong [1 ]
Semeraro, Quirico [1 ]
Matta, Andrea [1 ]
机构：
[1] Politecn Milan, Dipartimento Meccan, Milan, Italy
来源：
COMPUTERS & OPERATIONS RESEARCH | 2018年 / 100卷
关键词：
Scheduling; Hybrid flow shop; Genetic algorithm; SEQUENCE-DEPENDENT SETUP; PARALLEL MACHINES; TOTAL TARDINESS; SEARCH ALGORITHM; TIMES; FLOWSHOPS; SYSTEM; OPTIMIZATION; CONSTRAINTS; INDUSTRY;
D O I：
10.1016/j.cor.2018.07.025
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper presents a genetic algorithm to solve the hybrid flow shop scheduling problem to minimize the total tardiness. Practical assumptions as unrelated machines and machine eligibility are considered. The proposed algorithm incorporates a new decoding method developed for total tardiness objective, which is able to obtain tight schedule meanwhile guarantee the influence of the chromosome on the schedule. The proposed algorithm has been calibrated with a full factorial design of experiment, and compared to several calibrated state-of-art algorithms on 450 instances with different size and correlation patterns of operation processing time. The results validate the effectiveness of the proposed algorithm. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码：211 / 229
页数：19
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