A controlled genetic algorithm by fuzzy logic and belief functions for job-shop scheduling

被引：20
|
作者：
Hajri, S
Liouane, N
Hammadi, S
Borne, P
机构：
[1] Ecole Natl Ingenieurs Monastir, Monastir, Tunisia
[2] Ecole Cent Lille, LAIL, CNRS, URA D 1440, F-59651 Villeneuve Dascq, France
来源：
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS | 2000年 / 30卷 / 05期
关键词：
belief functions; fuzzy logic; genetic algorithm; job-shop scheduling;
D O I：
10.1109/3477.875454
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Most scheduling problems are highly complex combinatorial problems, However, stochastic methods such us genetic algorithm yield good solutions. In this paper, we present a controlled genetic algorithm (CGA) based on fuzzy logic and belief functions to solve job-shop scheduling problems. For better performance, we propose an efficient representational scheme, heuristic rules for creating the initial population, and a new methodology for mixing and computing genetic operator probabilities. A 10-jobs/6-machines example shows the effectiveness of the developed method.
引用
收藏
页码：812 / 818
页数：7
相关论文
共 50 条
  • [41] An immune-genetic algorithm for dynamic job-shop scheduling
    Chai, Yong-sheng
    Zhou, Yu-lan
    Chen, Yibao
    Zhu, Bin
    [J]. WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 7338 - 7342
  • [42] An improved adaptive genetic algorithm for job-shop scheduling problem
    Xing, Yingjie
    Chen, Zhentong
    Sun, Jing
    Hu, Long
    [J]. ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 4, PROCEEDINGS, 2007, : 287 - +
  • [43] A genetic algorithm for energy-efficiency in job-shop scheduling
    Salido, Miguel A.
    Escamilla, Joan
    Giret, Adriana
    Barber, Federico
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2016, 85 (5-8): : 1303 - 1314
  • [44] Improved genetic algorithm for the flexible job-shop scheduling problem
    Zhang, Guohui
    Gao, Liang
    Li, Peigen
    Zhang, Chaoyong
    [J]. Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2009, 45 (07): : 145 - 151
  • [45] A genetic algorithm for energy-efficiency in job-shop scheduling
    Miguel A. Salido
    Joan Escamilla
    Adriana Giret
    Federico Barber
    [J]. The International Journal of Advanced Manufacturing Technology, 2016, 85 : 1303 - 1314
  • [46] Genetic algorithm for job-shop scheduling with machine unavailability and breakdowns
    Hasan, S. M. Kamrul
    Sarker, Ruhul
    Essam, Daryl
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2011, 49 (16) : 4999 - 5015
  • [47] A Hybrid Genetic Algorithm for Flexible Job-shop Scheduling Problem
    Wang Shuang-xi
    Zhang Chao-yong
    Jin Liang-liang
    [J]. ENGINEERING SOLUTIONS FOR MANUFACTURING PROCESSES IV, PTS 1 AND 2, 2014, 889-890 : 1179 - 1184
  • [48] Genetic Algorithm Design and Simulation for Job-shop Scheduling Problem
    Wang, Gui Cong
    Tian, Xi Jie
    Ll, Chuan Peng
    Yang, Na Na
    [J]. MECHATRONICS AND APPLIED MECHANICS, PTS 1 AND 2, 2012, 157-158 : 1436 - 1440
  • [49] Solving Job-Shop Scheduling Problem with Improved Genetic Algorithm
    Wu, Weijun
    Yu, Songnian
    Ding, Wang
    [J]. PROCEEDINGS OF 2008 INTERNATIONAL PRE-OLYMPIC CONGRESS ON COMPUTER SCIENCE, VOL II: INFORMATION SCIENCE AND ENGINEERING, 2008, : 348 - 352
  • [50] An effective genetic algorithm for the flexible job-shop scheduling problem
    Zhang, Guohui
    Gao, Liang
    Shi, Yang
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (04) : 3563 - 3573
12345