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On the performance of task-oriented branch-and-bound algorithms for workload smoothing in simple assembly line balancing

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  • Rico Walter
  • Philipp Schulze

Abstract

Smoothing the workloads among the stations of an already installed assembly line is one of the major objectives in assembly line (re-)balancing. In order to find a feasible task-station assignment that distributes the total workload as equal as possible, two exact task-oriented branch-and-bound algorithms have recently been proposed. In this paper, we systematically analyse their effectiveness in solving the workload smoothing problem on simple assembly lines. In our experiments, we also examine the performance of a state-of-the-art mathematical programming solver and a ‘combined’ exact branch-and-bound procedure that integrates components of the two algorithms from the literature. In terms of theory, we show the equivalence of two recently developed local lower bounding arguments and suggest a slight improvement of the bound. We also propose an enhanced feasibility test.

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  • Rico Walter & Philipp Schulze, 2022. "On the performance of task-oriented branch-and-bound algorithms for workload smoothing in simple assembly line balancing," International Journal of Production Research, Taylor & Francis Journals, vol. 60(15), pages 4654-4667, August.
    • Handle: RePEc:taf:tprsxx:v:60:y:2022:i:15:p:4654-4667
    DOI: 10.1080/00207543.2021.1934589
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    Cited by:

    1. 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.

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