An effective DE algorithm for hybrid flow shop load balancing scheduling problem

被引：0
|
作者：
Han Zhonghua [1 ,2 ]
Dong Xiaoting [1 ]
Lin Shuo [1 ]
机构：
[1] Shenyang Jianzhu Univ, Fac Informat & Control Engn, Shenyang, Peoples R China
[2] Chinese Acad Sci, Dept Digital Factory, Shenyang Inst Automat, Shenyang, Peoples R China
来源：
PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON ELECTRONIC SCIENCE AND AUTOMATION CONTROL | 2015年 / 20卷
关键词：
HFS scheduling problem; load balancing; selection probability; DE algorithm; DPSADE algorithm;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, an improved DE algorithm called double population self-adaptive differential evolution (DPSADE) algorithm is used to solve the hybrid flow shop load balancing scheduling problem (HFS-LBSP) which combines a novel double population cooperative evolution mechanism with a special self-adaptive parameter adjusting strategy. A mathematical model in which the weighted summation of the processing time load balancing cost and the total parallel machine waiting time is set as load balancing comprehensive evaluation index is formulated for this problem. In the last, The comparison between DPSADE and DE, SADE demostrates the effectiveness of DPSADE in solving HFS-LBSP.
引用
收藏
页码：221 / 225
页数：5
相关论文
共 50 条
  • [21] An effective hybrid genetic algorithm for flow shop scheduling with limited buffers
    Wang, L
    Zhang, L
    Zheng, DZ
    COMPUTERS & OPERATIONS RESEARCH, 2006, 33 (10) : 2960 - 2971
  • [22] A hybrid algorithm to minimize makespan for the permutation flow shop scheduling problem
    Ahmadizar, Fardin
    Barzinpour, Farnaz
    INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2010, 3 (06) : 853 - 861
  • [23] Hybrid Flow-Shop Scheduling Problem Based on Genetic Algorithm
    Rong, Zhang
    PROCEEDINGS OF THE 2017 2ND INTERNATIONAL CONFERENCE ON MATERIALS SCIENCE, MACHINERY AND ENERGY ENGINEERING (MSMEE 2017), 2017, 123 : 1703 - 1706
  • [24] Hybrid Genetic Algorithm for Distributed Flow Shop Inverse Scheduling Problem
    Mu J.
    Duan P.
    Gao L.
    Peng W.
    Cong J.
    Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2022, 58 (06): : 295 - 308
  • [25] An effective hybrid teaching-learning-based optimization algorithm for permutation flow shop scheduling problem
    Xie, Zhanpeng
    Zhang, Chaoyong
    Shao, Xiniyu
    Lin, Wenwen
    Zhu, Haiping
    ADVANCES IN ENGINEERING SOFTWARE, 2014, 77 : 35 - 47
  • [26] A Hybrid Algorithm for Job Shop Scheduling Problem
    Toader, Florentina Alina
    STUDIES IN INFORMATICS AND CONTROL, 2015, 24 (02): : 171 - 180
  • [27] An Effective Hybrid Heuristic for Flow Shop Scheduling
    D.-Z. Zheng
    L. Wang
    The International Journal of Advanced Manufacturing Technology, 2003, 21 (1) : 38 - 44
  • [28] An effective hybrid heuristic for flow shop scheduling
    Wang, L. (wangling@mail.tsinghua.edu.cn), 1600, Springer-Verlag London Ltd (21):
  • [29] An effective hybrid heuristic for flow shop scheduling
    Wang, L
    Zheng, DZ
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2003, 21 (01): : 38 - 44
  • [30] An Effective DE-EDA for Permutation Flow-shop Scheduling Problem
    Li, Zuo-cheng
    Guo, Qingxin
    Tang, Lixin
    2016 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2016, : 2927 - 2934
12345