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Improved imperialist competitive algorithms for rebalancing multi-objective two-sided assembly lines with space and resource constraints

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  • Yahui Zhang
  • Xiaofeng Hu
  • Chuanxun Wu

Abstract

In this paper, a mathematical model and an improved imperial competition algorithm (IICA) are proposed to solve the multi-objective two-sided assembly line rebalancing problem with space and resource restrictions (MTALRBP-SR). The aim is to find lines’ rebalance with the trade-off between efficiency, rebalancing cost and smoothing after reconfiguration. IICA utilises a new initialisation heuristic procedure based on classic heuristic rules to generate feasible initial solutions. A novel heuristic assimilation method is developed to vigorously conduct local search. In addition, a group-based decoding heuristic procedure is developed to fulfil the final task reassignment with the additional restrictions. To investigate the performance of the proposed algorithm, it is first tested on MTALRBP of benchmark problems and compared with some existing algorithms such as genetic algorithm, variable neighbourhood search algorithm, discrete artificial bee colony algorithm, and two iterated greedy algorithms. Next, the efficiency of the proposed IICA for solving MTALRBP-SR is revealed by comparison with a non-dominated sorting genetic algorithm (NSGA-II) and two versions of original ICA. Computational results and comparisons show the efficiency and effectiveness of IICA. Furthermore, a real-world case study is conducted to validate the proposed algorithm.

Suggested Citation

  • Yahui Zhang & Xiaofeng Hu & Chuanxun Wu, 2020. "Improved imperialist competitive algorithms for rebalancing multi-objective two-sided assembly lines with space and resource constraints," International Journal of Production Research, Taylor & Francis Journals, vol. 58(12), pages 3589-3617, June.
    • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:12:p:3589-3617
    DOI: 10.1080/00207543.2019.1633023
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    Cited by:

    1. Boysen, Nils & Schulze, Philipp & Scholl, Armin, 2022. "Assembly line balancing: What happened in the last fifteen years?," European Journal of Operational Research, Elsevier, vol. 301(3), pages 797-814.
    2. Battaïa, Olga & Dolgui, Alexandre, 2022. "Hybridizations in line balancing problems: A comprehensive review on new trends and formulations," International Journal of Production Economics, Elsevier, vol. 250(C).

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