A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion

被引:185
|
作者
Gao, Kai Zhou [1 ]
Suganthan, Ponnuthurai Nagaratnam [1 ]
Chua, Tay Jin [2 ]
Chong, Chin Soon [2 ]
Cai, Tian Xiang [2 ]
Pan, Qan Ke [3 ]
机构
[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
[2] Singapore Inst Mfg Technol, Singapore 638075, Singapore
[3] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Peoples R China
基金
美国国家科学基金会;
关键词
Flexible job-shop scheduling; New job inserting; Artificial bee colony; Re-scheduling; OPTIMIZATION;
D O I
10.1016/j.eswa.2015.06.004
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study addresses the scheduling problem in remanufacturing engineering. The purpose of this paper is to model effectively to solve remanufacturing scheduling problem. The problem is modeled as flexible job-shop scheduling problem (FISP) and is divided into two stages: scheduling and re-scheduling when new job arrives. The uncertainty in timing of returns in remanufacturing is modeled as new job inserting constraint in FJSP. A two-stage artificial bee colony (TABC) algorithm is proposed for scheduling and re-scheduling with new job(s) inserting. The objective is to minimize makespan (maximum complete time). A new rule is proposed to initialize bee colony population. An ensemble local search is proposed to improve algorithm performance. Three re-scheduling strategies are proposed and compared. Extensive computational experiments are carried out using fifteen well-known benchmark instances with eight instances from remanufacturing. Forscheduling performance, TABC is compared to five existing algorithms. For re-scheduling performance, TABC is compared to six simple heuristics and proposed hybrid heuristics. The results and comparisons show that TABC is effective in both scheduling stage and rescheduling stage. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:7652 / 7663
页数:12
相关论文
共 50 条
  • [41] Bilevel genetic algorithm for the flexible job-shop scheduling problem
    Zhang, Chaoyong
    Rao, Yunqing
    Li, Peigen
    Shao, Xinyu
    Jixie Gongcheng Xuebao/Chinese Journal of Mechanical Engineering, 2007, 43 (04): : 119 - 124
  • [42] A heuristic algorithm for the distributed and flexible job-shop scheduling problem
    Mohsen Ziaee
    The Journal of Supercomputing, 2014, 67 : 69 - 83
  • [43] A heuristic algorithm for the distributed and flexible job-shop scheduling problem
    Ziaee, Mohsen
    JOURNAL OF SUPERCOMPUTING, 2014, 67 (01): : 69 - 83
  • [44] A hybrid and flexible genetic algorithm for the job-shop scheduling problem
    Ferrolho, Antonio
    Crisostomo, Manuel
    2007 INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN ROBOTICS AND AUTOMATION, 2007, : 178 - +
  • [45] An Estimation of Distribution Algorithm for the Flexible Job-Shop Scheduling Problem
    Wang, Shengyao
    Wang, Ling
    Zhou, Gang
    Xu, Ye
    ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE, 2012, 6839 : 9 - 16
  • [46] An Efficient Genetic Algorithm for Flexible Job-Shop Scheduling Problem
    Moghadam, Ali Mokhtari
    Wong, Kuan Yew
    Piroozfard, Hamed
    2014 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT (IEEM), 2014, : 1409 - 1413
  • [47] An effective genetic algorithm for the flexible job-shop scheduling problem
    Zhang, Guohui
    Gao, Liang
    Shi, Yang
    EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (04) : 3563 - 3573
  • [48] A Hybrid Genetic Algorithm for Flexible Job-shop Scheduling Problem
    Wang Shuang-xi
    Zhang Chao-yong
    Jin Liang-liang
    ENGINEERING SOLUTIONS FOR MANUFACTURING PROCESSES IV, PTS 1 AND 2, 2014, 889-890 : 1179 - 1184
  • [49] Improved genetic algorithm for the flexible job-shop scheduling problem
    Zhang, Guohui
    Gao, Liang
    Li, Peigen
    Zhang, Chaoyong
    Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2009, 45 (07): : 145 - 151
  • [50] A genetic algorithm for flexible job-shop scheduling
    Chen, HX
    Ihlow, J
    Lehmann, C
    ICRA '99: IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-4, PROCEEDINGS, 1999, : 1120 - 1125