Solving batch production scheduling using genetic algorithm

被引：0
|
作者：
Wu, LY [1 ]
Hu, YD [1 ]
Xu, DM [1 ]
Hua, B [1 ]
机构：
[1] Ocean Univ China, Coll Chem & Chem Engn, Qingdao 266003, Peoples R China
来源：
PROCESS SYSTEMS ENGINEERING 2003, PTS A AND B | 2003年 / 15卷
关键词：
production scheduling; batch process; combinatorial optimization; genetic algorithm;
D O I：
暂无
中图分类号：
TQ [化学工业];
学科分类号：
0817 ;
摘要：
The optimal scheduling of multi-product batch process is studied. The relationship between production scale and production cost is analyzed. A new mathematics model is proposed which takes the maximum profit as objective function, which can be solved by the modified genetic algorithm (GA) with mixed coding (sequence coding and decimal coding) developed by us. The PMX crossover and reverse mutation are used for the sequence coding. At the same time, the arithmetic crossover and heteropic mutation are used for the decimal coding. An example is solved to demonstrate the effectiveness of the method.
引用
收藏
页码：648 / 653
页数：6
相关论文
共 50 条
  • [41] Solving a concrete sleepers production scheduling by genetic algorithms
    Perez-Vazquez, M. E.
    Gento-Municio, A. M.
    Lourenco, H. R.
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 179 (03) : 605 - 620
  • [42] Optimization of the Master Production Scheduling in a Textile Industry Using Genetic Algorithm
    Lorente-Leyva, Leandro L.
    Murillo-Valle, Jefferson R.
    Montero-Santos, Yakcleem
    Herrera-Granda, Israel D.
    Herrera-Granda, Erick P.
    Rosero-Montalvo, Paul D.
    Peluffo-Ordonez, Diego H.
    Blanco-Valencia, Xiomara P.
    [J]. HYBRID ARTIFICIAL INTELLIGENT SYSTEMS, HAIS 2019, 2019, 11734 : 674 - 685
  • [43] OPTIMIZATION OF PRODUCTION SCHEDULING USING SELF-CROSSOVER GENETIC ALGORITHM
    Wu, Wanli
    Wang, Linyu
    Zhao, Fei
    Fan, Yiliang
    Xinliang
    Tang, Ruixin
    Yangxu
    Wen, Yongshen
    [J]. PROCEEDINGS OF 2019 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION (ICWAPR), 2019, : 79 - 85
  • [44] Integration of production planning and scheduling using an expert system and a genetic algorithm
    Lawrynowicz, A.
    [J]. JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 2008, 59 (04) : 455 - 463
  • [45] Production Scheduling using Augmented Lagrangian Relaxation and Genetic Algorithm Optimization
    Moosavi, E.
    Gholamnejad, J.
    Ataee-pour, M.
    Khorram, E.
    [J]. PROCEEDINGS OF THE 24TH INTERNATIONAL MINING CONGRESS AND EXHIBITION OF TURKEY, IMCET 2015, 2015, : 788 - 796
  • [46] Longest Jobs First Algorithm in Solving Job Shop Scheduling Using adaptive Genetic Algorithm(GA)
    Sahzabi, Vahid Alizadeh
    Karimi, Iman
    Sahzabi, Navid Alizadeh
    Barnaghi, Peiman Mamaani
    [J]. FOURTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2011): MACHINE VISION, IMAGE PROCESSING, AND PATTERN ANALYSIS, 2012, 8349
  • [47] Solving fuzzy job shop scheduling problems using random key genetic algorithm
    Lei, Deming
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2010, 49 (1-4): : 253 - 262
  • [48] A Method of Solving Scheduling Problems Using Genetic Algorithm with Improved Lagrangian Relaxation Method
    Wang, Xiaofei
    Wang, Wei
    Tamura, Hiroki
    Tang, Zheng
    [J]. INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2009, 9 (05): : 51 - 58
  • [49] Solving fuzzy job shop scheduling problems using random key genetic algorithm
    Deming Lei
    [J]. The International Journal of Advanced Manufacturing Technology, 2010, 49 : 253 - 262
  • [50] Solving Flow Shop Scheduling Problem Considering Waiting Time Using Genetic Algorithm
    Wang, Hongbing
    Xu, Anjun
    He, Dongfeng
    Yao, Lin
    [J]. MANUFACTURING ENGINEERING AND AUTOMATION I, PTS 1-3, 2011, 139-141 : 1684 - +
12345