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An Integer Programming Algorithm with Network Cuts for Solving the Assembly Line Balancing Problem

Author

Listed:
  • F. Brian Talbot

    (University of Michigan)

  • James H. Patterson

    (University of Missouri---Columbia; Nijenrode, The Netherlands School of Business)

Abstract

In this paper, we describe an integer programming algorithm for assigning tasks on an assembly line to work stations in such a way that the number of work stations is minimal for the rate of production desired. The procedure insures that no task is assigned to a work station before all tasks which technologically must be performed before it have been assigned (precedence restrictions are not violated), and that the total time required at each work station performing the tasks assigned to it does not exceed the time available (cycle time restrictions are not violated). The procedure is based on a systematic evaluation (enumeration) of all possible task assignments to work stations. Significant portions of the enumeration process are performed implicitly, however, by utilizing tests described in the paper which are based on the specific structure of the line balancing problem. An artifice termed a network cut is also developed which eliminates from explicit consideration the assignment of tasks to work stations where such assignments would not lead to improved line balances. Results reported demonstrate that the procedure can obtain optimal balances for assembly lines with between 50 and 100 tasks in a reasonable amount of computation time and with modest computer storage requirements.

Suggested Citation

  • F. Brian Talbot & James H. Patterson, 1984. "An Integer Programming Algorithm with Network Cuts for Solving the Assembly Line Balancing Problem," Management Science, INFORMS, vol. 30(1), pages 85-99, January.
    • Handle: RePEc:inm:ormnsc:v:30:y:1984:i:1:p:85-99
    DOI: 10.1287/mnsc.30.1.85
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    Citations

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    Cited by:

    1. Bukchin, Yossi & Raviv, Tal, 2018. "Constraint programming for solving various assembly line balancing problems," Omega, Elsevier, vol. 78(C), pages 57-68.
    2. Chen, Ruey-Shun & Lu, Kun-Yung & Tai, Pei-Hao, 2004. "Optimizing assembly planning through a three-stage integrated approach," International Journal of Production Economics, Elsevier, vol. 88(3), pages 243-256, April.
    3. Miltenburg, John, 1998. "Balancing U-lines in a multiple U-line facility," European Journal of Operational Research, Elsevier, vol. 109(1), pages 1-23, August.
    4. Klein, Robert & Scholl, Armin, 1996. "Maximizing the production rate in simple assembly line balancing -- A branch and bound procedure," European Journal of Operational Research, Elsevier, vol. 91(2), pages 367-385, June.
    5. Kenneth H. Doerr & Theodore D. Klastorin & Michael J. Magazine, 2000. "Synchronous Unpaced Flow Lines with Worker Differences and Overtime Cost," Management Science, INFORMS, vol. 46(3), pages 421-435, March.
    6. Kara, Yakup & Paksoy, Turan & Chang, Ching-Ter, 2009. "Binary fuzzy goal programming approach to single model straight and U-shaped assembly line balancing," European Journal of Operational Research, Elsevier, vol. 195(2), pages 335-347, June.
    7. Boysen, Nils & Fliedner, Malte, 2008. "A versatile algorithm for assembly line balancing," European Journal of Operational Research, Elsevier, vol. 184(1), pages 39-56, January.
    8. Pinnoi, Anulark & Wilhelm, Wilbert E., 2000. "Valid inequalities for a class of assembly system problems," European Journal of Operational Research, Elsevier, vol. 126(1), pages 31-50, October.
    9. Kucukkoc, Ibrahim & Zhang, David Z., 2014. "Mathematical model and agent based solution approach for the simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines," International Journal of Production Economics, Elsevier, vol. 158(C), pages 314-333.
    10. Sawik, Tadeusz, 1998. "A lexicographic approach to bi-objective loading of a flexible assembly system," European Journal of Operational Research, Elsevier, vol. 107(3), pages 656-668, June.
    11. Aase, Gerald R. & Olson, John R. & Schniederjans, Marc J., 2004. "U-shaped assembly line layouts and their impact on labor productivity: An experimental study," European Journal of Operational Research, Elsevier, vol. 156(3), pages 698-711, August.
    12. Schulze, Philipp & Scholl, Armin & Walter, Rico, 2024. "R-SALSA: A branch, bound, and remember algorithm for the workload smoothing problem on simple assembly lines," European Journal of Operational Research, Elsevier, vol. 312(1), pages 38-55.
    13. Walter, Rico & Schulze, Philipp & Scholl, Armin, 2021. "SALSA: Combining branch-and-bound with dynamic programming to smoothen workloads in simple assembly line balancing," European Journal of Operational Research, Elsevier, vol. 295(3), pages 857-873.
    14. Urban, Timothy L. & Chiang, Wen-Chyuan, 2006. "An optimal piecewise-linear program for the U-line balancing problem with stochastic task times," European Journal of Operational Research, Elsevier, vol. 168(3), pages 771-782, February.
    15. Kucukkoc, Ibrahim & Li, Zixiang & Karaoglan, Aslan D. & Zhang, David Z., 2018. "Balancing of mixed-model two-sided assembly lines with underground workstations: A mathematical model and ant colony optimization algorithm," International Journal of Production Economics, Elsevier, vol. 205(C), pages 228-243.
    16. Scholl, Armin & Becker, Christian, 2006. "State-of-the-art exact and heuristic solution procedures for simple assembly line balancing," European Journal of Operational Research, Elsevier, vol. 168(3), pages 666-693, February.
    17. Scholl, Armin & Klein, Robert, 1999. "Balancing assembly lines effectively - A computational comparison," European Journal of Operational Research, Elsevier, vol. 114(1), pages 50-58, April.
    18. Lapierre, Sophie D. & Ruiz, Angel & Soriano, Patrick, 2006. "Balancing assembly lines with tabu search," European Journal of Operational Research, Elsevier, vol. 168(3), pages 826-837, February.
    19. Amen, Matthias, 2006. "Cost-oriented assembly line balancing: Model formulations, solution difficulty, upper and lower bounds," European Journal of Operational Research, Elsevier, vol. 168(3), pages 747-770, February.

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