An effective discrete harmony search algorithm for flexible job shop scheduling problem with fuzzy processing time

被引：87
|
作者：
Gao, Kai Zhou [1 ,2 ]
Suganthan, Ponnuthurai Nagaratnam [1 ]
Pan, Quan Ke [2 ]
Tasgetiren, Mehmet Fatih [3 ]
机构：
[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
[2] Liaocheng Univ, Sch Comp, Liaocheng, Peoples R China
[3] Yasar Univ, Dept Ind Engn, Izmir, Turkey
来源：
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH | 2015年 / 53卷 / 19期
基金：
美国国家科学基金会;
关键词：
discrete harmony search; flexible job shop scheduling; fuzzy processing time; fuzzy completion time; remanufacturing; GENETIC ALGORITHM; OPTIMIZATION ALGORITHM; FLOW-SHOP; COLONY;
D O I：
10.1080/00207543.2015.1020174
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This study addresses flexible job shop scheduling problem (FJSP) with fuzzy processing time. The fuzzy or uncertainty of processing time is one of seven characteristics in remanufacturing. A discrete harmony search (DHS) algorithm is proposed for FJSP with fuzzy processing time. The objective is to minimise maximum fuzzy completion time. A simple and effective heuristic rule is proposed to initialise harmony population. Extensive computational experiments are carried out using five benchmark cases with eight instances from remanufacturing. The proposed heuristic rule is evaluated using five benchmark cases. The proposed DHS algorithm is compared to six metaheuristics. The results and comparisons show the effectiveness and efficiency of DHS for solving FJSP with fuzzy processing time.
引用
收藏
页码：5896 / 5911
页数：16
相关论文
共 50 条
  • [31] Solving fuzzy flexible job shop scheduling problems using genetic algorithm
    Lei, De-Ming
    Guo, Xiu-Ping
    PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2008, : 1014 - +
  • [32] Co-evolutionary genetic algorithm for fuzzy flexible job shop scheduling
    Lei, Deming
    APPLIED SOFT COMPUTING, 2012, 12 (08) : 2237 - 2245
  • [33] An effective multi-objective discrete virus optimization algorithm for flexible job-shop scheduling problem with controllable processing times
    Lu, Chao
    Li, Xinyu
    Gao, Liang
    Liao, Wei
    Yi, Jin
    COMPUTERS & INDUSTRIAL ENGINEERING, 2017, 104 : 156 - 174
  • [34] A hybrid discrete particle swarm optimization algorithm for solving fuzzy job shop scheduling problem
    Li, Jun-qing
    Pan, Yu-xia
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2013, 66 (1-4): : 583 - 596
  • [35] An improved genetic algorithm for the flexible job shop scheduling problem with multiple time constraints
    Zhang, Guohui
    Hu, Yifan
    Sun, Jinghe
    Zhang, Wenqiang
    SWARM AND EVOLUTIONARY COMPUTATION, 2020, 54
  • [36] An improved genetic algorithm for the flexible job shop scheduling problem with multiple time constraints
    Zhang G.
    Hu Y.
    Sun J.
    Zhang W.
    Swarm and Evolutionary Computation, 2020, 54
  • [37] Self-adaptive multi-objective evolutionary algorithm for flexible job shop scheduling with fuzzy processing time
    Li, Rui
    Gong, Wenyin
    Lu, Chao
    COMPUTERS & INDUSTRIAL ENGINEERING, 2022, 168
  • [38] Swarm-based neighbourhood search algorithm for fuzzy flexible job shop scheduling
    Lei, Deming
    Guo, Xiuping
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2012, 50 (06) : 1639 - 1649
  • [39] A Hybrid Cooperative Coevolution Algorithm for Fuzzy Flexible Job Shop Scheduling
    Sun, Lu
    Lin, Lin
    Gen, Mitsuo
    Li, Haojie
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2019, 27 (05) : 1008 - 1022
  • [40] A simple and effective evolutionary algorithm for multiobjective flexible job shop scheduling
    Chiang, Tsung-Che
    Lin, Hsiao-Jou
    INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2013, 141 (01) : 87 - 98
12345