Skip to main content
SpringerLink
Log in

Multi-rule Multi-objective Simulated Annealing Algorithm for Straight and U Type Assembly Line Balancing Problems

  • Published:
Journal of Intelligent Manufacturing Aims and scope Submit manuscript

Abstract

The task of balancing of assembly lines is of considerable industrial importance. It consists of assigning operations to workstations in a production line in such a way that (1) no assembly precedence constraint is violated, (2) no workstations in the line takes longer than a predefined cycle time to perform all tasks assigned to it, and (3) as few workstations as possible are needed to perform all the tasks in the set. This paper presents a new multiple objective simulated annealing (SA) algorithm for simple (line) and U type assembly line balancing problems with the aim of maximizing “smoothness index” and maximizing the “line performance” (or minimizing the number of workstations). The proposed algorithm makes use of task assignment rules in constructing feasible solutions. The proposed algorithm is tested and compared with literature test problems. The proposed algorithm found the optimal solutions for each problem in short computational times. A detailed performance analysis of the selected task assignment rules is also given in the paper.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Ajenblit, D. A., & Wainwright, R. L. (1998). Applying genetic algorithms to the U-shaped assembly line balancing problem. Proceedings of the 1998 IEEE international conference on evolutionary computation, Anchorage, Alaska, pp. 96–101

  • A. L. Arcus (1966) ArticleTitleCOMSOAL: A computer method of sequencing operations for assembly lines International Journal of Production Research 4 259–277

    Google Scholar 

  • F.F. Boctor (1995) ArticleTitleA multiple-rule heuristic for assembly line balancing Journal of Operational Research Society 46 62–69

    Google Scholar 

  • I. Baybars (1986) ArticleTitleA survey of exact algorithms for the simple assembly line balancing problem Management Science 32 IssueID8 909–932

    Google Scholar 

  • Baykasoglu, A., Dereli, T., Sabuncu, I. (2005). A multiple objective ant colony optimization approach to assembly line balancing problems, CIE35 35th International Conference on Computers and Industrial Engineering, 19-22 June 2005, Istanbul, pp. 263–268.

  • A. Baykasoglu (2005) ArticleTitlePreemptive goal programming using simulated annealing Engineering Optimization 37 IssueID1 49–63

    Google Scholar 

  • Baykasoglu, A., Özbak\(\imath\)r, L., & Telcioglu, M. B. (2002). Multiple-rule based genetic algorithm for simple assembly line balancing problems (MRGA-SALBP-I), Proceedings of the 5th international conference on managing innovations in manufacturing (MIM) 2002, Milwaukee, Wisconsin, USA, pp. 402–408

  • C. Becker A. Scholl (2006) ArticleTitleA survey on problems and methods in generalized assembly line balancing European Journal of Operational Research 168 IssueID3 694–715 Occurrence Handle10.1016/j.ejor.2004.07.023

    Article  Google Scholar 

  • K. C. C. Chan P. C. L. Hui K. W. Yeung F. S. F. Ng (1998) ArticleTitleHandling the assembly line balancing problem in the clothing industry using a genetic algorithm International Journal of Clothing Science and Technology 10 IssueID1 21–37 Occurrence Handle10.1108/09556229810205240

    Article  Google Scholar 

  • W.-C. Chiang (1998) ArticleTitleThe application of a tabu search metaheuristic to the assembly line balancing problem Annals of Operations Research 77 209–227 Occurrence Handle10.1023/A:1018925411397

    Article  Google Scholar 

  • E. A. Elsayed T. O. Boucher (1994) Analysis and control of production systems Prentice Hall International Series in Industrial and Systems Engineering New Jersey

    Google Scholar 

  • E. Erel S. C. Sarin (1998) ArticleTitleA survey of the assembly line balancing procedures Production Planning & Control 9 IssueID5 414–434

    Google Scholar 

  • E. Erel I. Sabuncuoglu B. A. Aksu (2001) ArticleTitleBalancing of U-type assembly systems using simulated annealing International Journal of Production Research 39 IssueID13 3003–3015

    Google Scholar 

  • S. Ghosh R. J. Gagnon (1989) ArticleTitleA comprehensive literature review and analysis of the design, balancing and scheduling of assembly systems International Journal of Production Research 27 637–670

    Google Scholar 

  • J. F. Goncalves J. R. D. Almeida (2002) ArticleTitleA hybrid genetic algorithm for assembly line balancing Journal of Heuristics 8 629–642

    Google Scholar 

  • W. Helgeson D. Birnie (1961) ArticleTitleAssembly line balancing using the ranked positional weight technique Journal of Industrial Engineering 12 394–398

    Google Scholar 

  • Y. J. Kim Y. K. Kim Y. Cho (1998) ArticleTitleA heuristic-based genetic algorithm for workload smoothing in assembly lines Computers & Operations Research 25 IssueID2 99–111 Occurrence Handle10.1016/S0305-0548(97)00046-4

    Article  Google Scholar 

  • S. Kirkpatrick C. D. Gelatt M. P. Vecchi (1983) ArticleTitleOptimization by simulated annealing Science 220 671–680

    Google Scholar 

  • P. R. McMullen P. Tarasewich (2003) ArticleTitleUsing ant techniques to solve the assembly line balancing problem IIE Transactions 35 605–617 Occurrence Handle10.1080/07408170304354

    Article  Google Scholar 

  • J. Miltenburg (2001) ArticleTitleU-shaped production lines: A review of theory and practice International Journal of Production Economics 70 201–214 Occurrence Handle10.1016/S0925-5273(00)00064-5

    Article  Google Scholar 

  • G. J. Miltenburg J. Wijngaard (1994) ArticleTitleThe U-line line balancing problem Management Science 40 1378–1988

    Google Scholar 

  • S. Ponnambalam G. Aravindan G. Mogileeswar Naidu (2000) ArticleTitleA multi-objective genetic algorithm for solving assembly line balancing problem International Journal of Advanced Manufacturing Technology 16 341–352

    Google Scholar 

  • I. Sabuncuoglu E. Erel M. Tanyer (2000) ArticleTitleAssembly line balancing using genetic algorithms Journal of Intelligent Manufacturing 11 295–310 Occurrence Handle10.1023/A:1008923410076

    Article  Google Scholar 

  • M. E. Salveson (1955) ArticleTitleThe assembly line balancing problem Journal of Industrial Engineering 6 18–25

    Google Scholar 

  • A. Scholl C. Becker (2006) ArticleTitleState-of-the-art exact and heuristic solution procedures for simple assembly line balancing European Journal of Operational Research 168 IssueID3 666–693 Occurrence Handle10.1016/j.ejor.2004.07.022

    Article  Google Scholar 

  • A. Scholl R. Klein (1999) ArticleTitleBalancing assembly lines effectively: A computational comparison European Journal of Operational Research 114 50–58 Occurrence Handle10.1016/S0377-2217(98)00173-8

    Article  Google Scholar 

  • A. Scholl S. Voß (1996) ArticleTitleSimple assembly line balancing-heuristic approaches Journal of Heuristics 2 IssueID3 217–244

    Google Scholar 

  • F. B. Talbot J. H. Patterson W. V. Gehrlein (1986) ArticleTitleA comparative evaluation of heuristic line balancing techniques Management Science 32 430–454

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, University of Gaziantep, 27310, Gaziantep, Turkey

    Adil Baykasoglu

Authors
  1. Adil Baykasoglu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Adil Baykasoglu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Baykasoglu, A. Multi-rule Multi-objective Simulated Annealing Algorithm for Straight and U Type Assembly Line Balancing Problems. J Intell Manuf 17, 217–232 (2006). https://doi.org/10.1007/s10845-005-6638-y

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10845-005-6638-y

Keywords

Search

Navigation