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The two-stage assembly flowshop scheduling problem with bicriteria of makespan and mean completion time

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Abstract

In this paper, we address the two-stage assembly flowshop scheduling problem with a weighted sum of makespan and mean completion time criteria, known as bicriteria. Since the problem is NP-hard, we propose heuristics to solve the problem. Specifically, we propose three heuristics; simulated annealing (SA), ant colony optimization (ACO), and self-adaptive differential evolution (SDE). We have conducted computational experiments to compare the performance of the proposed heuristics. It is statistically shown that both SA and SDE perform better than ACO. Moreover, the experiments reveal that SA, in general, performs better than SDE, while SA consumes less CPU time than both SDE and ACO. Therefore, SA is shown to be the best heuristic for the problem.

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Authors and Affiliations

  1. Department of Industrial and Management Systems Engineering, Kuwait University, P.O. Box 5969, Safat, Kuwait

    Ali Allahverdi

  2. Department of Computer Engineering, Kuwait University, P.O. Box 5969, Safat, Kuwait

    Fawaz S. Al-Anzi

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  1. Ali Allahverdi
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  2. Fawaz S. Al-Anzi
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Correspondence to Ali Allahverdi.

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Allahverdi, A., Al-Anzi, F.S. The two-stage assembly flowshop scheduling problem with bicriteria of makespan and mean completion time. Int J Adv Manuf Technol 37, 166–177 (2008). https://doi.org/10.1007/s00170-007-0950-y

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  • DOI: https://doi.org/10.1007/s00170-007-0950-y

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