Survey on genetic algorithms for solving flexible job-shop scheduling problem

被引：0
|
作者：
Huang X. [1 ]
Chen S. [1 ]
Zhou T. [1 ]
Sun Y. [1 ]
机构：
[1] Faculty of Economics and Management, Dalian University of Technology, Dalian
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2022年 / 28卷 / 02期
关键词：
Chromosome representation; Flexible job-shop scheduling problem; Genetic algorithms; Genetic operation;
D O I：
10.13196/j.cims.2022.02.018
中图分类号：
学科分类号：
摘要：
Flexible Job-Shop Scheduling Problem (FJSP) is an important scheduling problem with extensive applications. As one of the most popular methods for solving FJSP, Genetic algorithms (GAs) have attracted significant attentions of a number of researchers. A survey of recent works on GAs for solving FJSP was given, especially five main chromosome representations and relevant crossover and mutation operators in GAs. Then seven evaluation criteria including encoding feasibility, mapping relation, memory space, decoding complexity, encoding completeness, the complexity of genetic operation and the diversity of genetic operation were proposed to evaluate the five chromosome representations. © 2022, Editorial Department of CIMS. All right reserved.
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页码：536 / 551
页数：15
相关论文
共 70 条
  • [1] BLAZEWICZ J, FINKE G, HAUPT R, Et al., New trends in machine scheduling[J], European Journal of Operational Research, 37, 3, pp. 303-317, (1988)
  • [2] LI X Y, GAO L., An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem[J], International Journal of Production Economics, 174, pp. 93-110, (2016)
  • [3] ZHAO Shikui, FANG Shuiliang, GU Xinjian, Idle time neighborhood search genetic algorithm for job shop scheduling, Computer Integrated Manufacturing Systems, 20, 8, pp. 1930-1940, (2014)
  • [4] LUAN Fei, WANG Wen, FU Weiping, Et al., FJSP solving by improved GA based on PST hierarchy structure, Computer Integrated Manufacturing Systems, 20, 10, pp. 2494-2501, (2014)
  • [5] WU Xiuli, SUN Yangjun, Flexible job shop green scheduling problem with multi-speed machine, Computer Integrated Manufacturing Systems, 24, 4, pp. 862-875, (2018)
  • [6] ZHANG G, HU Y, SUN J, Et al., An improved genetic algorithm for the flexible job shop scheduling problem with multiple time constraints[J], Swarm and Evolutionary Computation, 54, (2020)
  • [7] SHEN L, DAUZERE-PERES S, NEUFELD J S., Solving the flexible job shop scheduling problem with sequence-dependent setup times, European Journal of Operational Research, 265, 2, pp. 503-516, (2018)
  • [8] PALACIOS J J, GONZALEZ M A, VELA C R, Et al., Genetic tabu search for the fuzzy flexible job shop problem[J], Computers & Operations Research, 54, pp. 74-89, (2015)
  • [9] BRANDIMARTE P., Routing and scheduling in a flexible job shop by tabu search[J], Annals of Operations Research, 41, 3, pp. 157-183, (1993)
  • [10] CHEN Cheng, XING Lining, GA-ACO for solving flexible job shop scheduling problem, Computer Integrated Manufacturing Systems, 17, 3, pp. 615-621, (2011)
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