Solving job shop scheduling problems using artificial immune system

被引：0
|
作者：
Chandrasekaran, M. [1 ]
Asokan, P. [1 ]
Kumanan, S. [1 ]
Balamurugan, T. [1 ]
Nickolas, S. [2 ]
机构：
[1] Department of Production Engineering, National Institute of Technology, Tiruchirappalli, 620015 Tamilnadu, India
[2] Department of Computer Applications, National Institute of Technology, Tiruchirappalli, 620015 Tamilnadu, India
来源：
International Journal of Advanced Manufacturing Technology | 2006年 / 31卷 / 5-6期
关键词：
The n-job; m-machine job shop scheduling ([!text type='JS']JS[!/text]S) problem is one of the general production scheduling problems. Many existing heuristics give solutions for small size problems with near optimal solutions. This paper deals with the criterion of makespan minimization for the job shop scheduling of different size problems. The proposed computational method of artificial immune system algorithm (AIS) is used for finding optimal makespan values of different size problems. The artificial immune system algorithm is tested with 130 benchmark problems [10 (ORB1-ORB5 & ARZ5-ARZ9); 40 (LA01-LA40) and 80 (TA01-TA80)]. The results show that the AIS algorithm is an efficient and effective algorithm which gives better results than the Tabu search shifting bottleneck procedure (TSSB) as well as the best solution of shifting bottleneck procedure ( SB-GLS1 ) of Balas and Vazacopoulos. © Springer-Verlag London Limited 2006;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Journal article (JA)
引用
收藏
页码：580 / 593
相关论文
共 50 条
  • [41] A New Artificial Immune Algorithm for Flexible Job-shop Scheduling
    Hong Lu
    NANOTECHNOLOGY AND COMPUTER ENGINEERING, 2010, 121-122 : 266 - 270
  • [42] A Three-fold Approach to Solve Dynamic Job Shop Scheduling Problems by Artificial Immune Algorithm
    Wu, Shanshan
    Li, Beizhi
    Yang, Jianguo
    MANUFACTURING ENGINEERING AND AUTOMATION I, PTS 1-3, 2011, 139-141 : 1666 - 1669
  • [43] Applying a hybrid artificial immune systems to the job shop scheduling problem
    Gary Weckman
    Akshata A. Bondal
    Magda M. Rinder
    William A. Young
    Neural Computing and Applications, 2012, 21 : 1465 - 1475
  • [44] An artificial immune algorithm for the flexible job-shop scheduling problem
    Bagheri, A.
    Zandieh, M.
    Mahdavi, Iraj
    Yazdani, M.
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2010, 26 (04): : 533 - 541
  • [45] On The Effectiveness Of Bottleneck Information For Solving Job Shop Scheduling Problems Using Deep Reinforcement Learning
    de Puiseau, Constantin Waubert
    Zey, Lennart
    Demir, Merve
    Tercan, Hasan
    Meisen, Tobias
    PROCEEDINGS OF THE CONFERENCE ON PRODUCTION SYSTEMS AND LOGISTICS, CPSL 2023-2, 2023, : 738 - 749
  • [46] Solving Fuzzy Job Shop Scheduling Problems with Availability Constraints Using a Scatter Search Method
    Engin, Orhan
    Yilmaz, M. Kerim
    Baysal, M. Emin
    Sarucan, Ahmet
    JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING, 2013, 21 (3-4) : 317 - 334
  • [47] Solving job insertion problem in job shop scheduling using iterative improvement
    Chiang, TW
    Hau, HY
    INFORMATION INTELLIGENCE AND SYSTEMS, VOLS 1-4, 1996, : 1525 - 1530
  • [48] A new approach to solve hybrid flow shop scheduling problems by artificial immune system
    Engin, O
    Döyen, A
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2004, 20 (06): : 1083 - 1095
  • [49] Research on immune genetic algorithm for solving the job-shop scheduling problem
    Xu, Xiao-Dong
    Li, Cong-Xin
    International Journal of Advanced Manufacturing Technology, 2007, 34 (7-8): : 783 - 789
  • [50] Research on immune genetic algorithm for solving the job-shop scheduling problem
    Xiao-dong Xu
    Cong-xin Li
    The International Journal of Advanced Manufacturing Technology, 2007, 34 : 783 - 789
12345