A scatter search based hyper-heuristic for sequencing a mixed-model assembly line

被引:29
|
作者
Cano-Belman, Jaime [1 ]
Rios-Mercado, Roger Z.
Bautista, Joaquin [2 ]
机构
[1] Univ Autonoma Nuevo Leon, Grad Program Syst Engn, San Nicolas De Los Garza 66450, NL, Mexico
[2] Univ Politecn Cataluna, UPC Nissan Chair, E-08028 Barcelona, Spain
关键词
Just-in-time scheduling; Assembly line; Priority rules; Work overload; Scatter search; Hyper-heuristic; MINIMUM JOB SETS; WORK OVERLOAD; ALGORITHM;
D O I
10.1007/s10732-009-9118-2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We address a mixed-model assembly-line sequencing problem with work overload minimization criteria. We consider time windows in work stations of the assembly line (closed stations) and different versions of a product to be assembled in the line, which require different processing time according to the work required in each work station. In a paced assembly line, products are feeded in the line at a predetermined constant rate (cycle time). Then, if many products with processing time greater than cycle time are feeded consecutively, work overload can be produced when the worker has insufficient time to finish his/her job. We propose a scatter search based hyper-heuristic for this NP-hard problem. In the low-level, the procedure makes use of priority rules through a constructive procedure. Computational experiments over a wide range of instances from the literature show the effectiveness of the proposed hyper-heuristics when compared to existing heuristics. The relevance of the priority rules was evaluated as well.
引用
收藏
页码:749 / 770
页数:22
相关论文
共 50 条
  • [41] Workforce minimization for a mixed-model assembly line in the automotive industry
    Battaia, Olga
    Delorme, Xavier
    Dolgui, Alexandre
    Hagemann, Johannes
    Horlemann, Anika
    Kovalev, Sergey
    Malyutin, Sergey
    INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2015, 170 : 489 - 500
  • [42] Assessing process time estimation for job sequencing in moving mixed-model assembly lines
    Alfaiz F.S.
    Kim D.S.
    Vergara H.A.
    International Journal of Industrial and Systems Engineering, 2024, 46 (02) : 215 - 237
  • [43] An Estimation of Distribution Algorithm-Based Hyper-Heuristic for the Distributed Assembly Mixed No-Idle Permutation Flowshop Scheduling Problem
    Zhao, Fuqing
    Zhu, Bo
    Wang, Ling
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2023, 53 (09): : 5626 - 5637
  • [44] A PSO-based Hyper-heuristic for Evolving Dispatching Rules in Job Shop Scheduling
    Su Nguyen
    Zhang, Mengjie
    2017 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2017, : 882 - 889
  • [45] Emperical Analysis of Hyper-heuristic Search Algorithms in Expensive Numerical Optimzation
    Ong, Jia Hui
    Teo, Jason
    2017 IEEE SYMPOSIUM ON COMPUTER APPLICATIONS & INDUSTRIAL ELECTRONICS (ISCAIE), 2017, : 117 - 121
  • [46] Integrating neural networks and logistic regression to underpin hyper-heuristic search
    Li, Jingpeng
    Burke, Edmund K.
    Qu, Rong
    KNOWLEDGE-BASED SYSTEMS, 2011, 24 (02) : 322 - 330
  • [47] Design of QOS based Web Service Selection/Composition Hyper-Heuristic Model
    Muthuraman, Sangeetha
    Venkatesan, V. Prasanna
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INFORMATICS AND ANALYTICS (ICIA' 16), 2016,
  • [48] The Effect of Pheromone in Ant-based Hyper-heuristic
    Abd Aziz, Zalilah
    ADVANCED RESEARCH IN MATERIAL SCIENCE AND MECHANICAL ENGINEERING, PTS 1 AND 2, 2014, 446-447 : 1202 - 1206
  • [49] A Sequence-based Selection Hyper-heuristic Utilising a Hidden Markov Model
    Kheiri, Ahmed
    Keedwell, Ed
    GECCO'15: PROCEEDINGS OF THE 2015 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 2015, : 417 - 424
  • [50] Development on Harmony Search Hyper-heuristic Framework for Examination Timetabling Problem
    Anwar, Khairul
    Khader, Ahamad Tajudin
    Al-Betar, Mohammed Azmi
    Awadallah, Mohammed A.
    ADVANCES IN SWARM INTELLIGENCE, ICSI 2014, PT II, 2014, 8795 : 87 - 95