Multi-objective genetic algorithm for integrated process planning and scheduling with fuzzy processing time

被引：0
|
作者：
Wen, Xiaoyu [1 ]
Li, Xinyu [1 ]
Gao, Liang [1 ]
Wan, Liang [1 ]
Wang, Wenwen [1 ]
机构：
[1] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Peoples R China
来源：
2013 SIXTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI) | 2013年
关键词：
Integrated process planning and scheduling; multi-objective genetic algorithm; fuzzy processing time;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Integrated process planning and scheduling is a significant research focus in recent years, which could improve the performance of manufacturing system. In real manufacturing environment, multi-objectives should be taken into consideration simultaneously during the machining process. Meanwhile, the processing time for each job is often imprecise in many real applications. Therefore, multi-objective integrated process planning and scheduling (IPPS) problem with fuzzy processing time is addressed in this paper. The processing time is described as triangular fuzzy number. A multi-objective genetic algorithm (MOGA) is designed to search for the Pareto solutions of multiobjective IPPS problem with fuzzy processing time. An instance has been designed to test the performance of proposed algorithm. The experiment result shows that the proposed MOGA could obtain satisfactory Pareto solutions for the multi-objective IPPS problem with fuzzy processing time.
引用
收藏
页码：293 / 298
页数：6
相关论文
共 50 条
  • [41] On Stockpile Planning Using a Multi-Objective Genetic Algorithm
    Pall, Raman
    Cheung, Edward
    2011 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE FOR MEASUREMENT SYSTEMS AND APPLICATIONS (CIMSA), 2011, : 29 - 33
  • [42] A novel fuzzy model for multi-objective permutation flow shop scheduling problem with fuzzy processing time
    Yuan, Fuyu
    Xu, Xin
    Yin, Minghao
    ADVANCES IN MECHANICAL ENGINEERING, 2019, 11 (04)
  • [43] An improved genetic algorithm for integrated process planning and scheduling
    Qiao Lihong
    Lv Shengping
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2012, 58 (5-8): : 727 - 740
  • [44] An improved genetic algorithm for integrated process planning and scheduling
    Qiao Lihong
    Lv Shengping
    The International Journal of Advanced Manufacturing Technology, 2012, 58 : 727 - 740
  • [45] A hybrid genetic approach for solving an integrated multi-objective operating room planning and scheduling problem
    Guido, Rosita
    Conforti, Domenico
    COMPUTERS & OPERATIONS RESEARCH, 2017, 87 : 270 - 282
  • [46] A Multi-Objective Model of Integrated Collaborative Planning and Scheduling for Dual-Resource and Its Algorithm
    Wang, Weizhong
    Ma, Chencheng
    Bao, Zhenqiang
    Ren, Xiaoqing
    2016 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT HUMAN-MACHINE SYSTEMS AND CYBERNETICS (IHMSC), VOL. 1, 2016, : 400 - 403
  • [47] Particle swarm optimization hybridized with genetic algorithm for uncertain integrated process planning and scheduling with interval processing time
    Li, Xinyu
    Gao, Liang
    Wang, Wenwen
    Wang, Cuiyu
    Wen, Long
    COMPUTERS & INDUSTRIAL ENGINEERING, 2019, 135 : 1036 - 1046
  • [48] Integrated multi-objective process planning and flexible job shop scheduling considering precedence constraints
    Shokouhi, Elahe
    PRODUCTION AND MANUFACTURING RESEARCH-AN OPEN ACCESS JOURNAL, 2018, 6 (01): : 61 - 89
  • [49] An improved multi-objective genetic algorithm for fuzzy flexible job-shop scheduling problem
    Wang, Xiaojuan
    Li, Wenfeng
    Zhang, Ying
    INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 2013, 47 (2-3) : 280 - 288
  • [50] Multi-objective genetic algorithm and its applications to flowshop scheduling
    Murata, T
    Ishibuchi, H
    Tanaka, H
    COMPUTERS & INDUSTRIAL ENGINEERING, 1996, 30 (04) : 957 - 968
12345