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A comparative study of exact methods for the simple assembly line balancing problem

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Abstract

Exact methods have shown advanced and promising performance in solving the simple assembly line balancing problem, known as NP-hard. This research investigates the impact of various structural parameters on the performance of exact methods, including branching methods, search direction, method to achieve upper bounds, utilized lower bounds, utilized dominance rules and search strategy. In accordance with the structural parameter evaluation, utilized dominance rules and search strategy have shown the most important effect on the exact methods’ performance. This research also improves and re-implements three well-known exact methods [i.e., SALOME, bounded dynamic programming (BDP) heuristic and branch, bound and remember (BBR) algorithm] using effective parameters. Computational study demonstrates that the utilization of high-performance structural parameters enhances the performance of exact methods by a significant margin. The re-implemented BBR method with proper parameters shows clear superiority over all the published exact methods and might be regarded as the state-of-the-art exact methodology.

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Acknowledgements

This study is supported by National Natural Science Foundation of China under Grant 61803287 and China Postdoctoral Science Foundation under Grant 2018M642928.

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Correspondence to Ibrahim Kucukkoc.

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Zixiang Li, Ibrahim Kucukkoc and Qiuhua Tang declare that they have no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Li, Z., Kucukkoc, I. & Tang, Q. A comparative study of exact methods for the simple assembly line balancing problem. Soft Comput (2019). https://doi.org/10.1007/s00500-019-04609-9

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Keywords

  • Assembly line balancing
  • Combinatorial optimization
  • Heuristics
  • Branch and bound