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An improved construction approach using ant colony optimization for solving the dynamic facility layout problem

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  • Pierrette P. Zouein
  • Sarah Kattan

Abstract

This paper presents an improved Ant Colony Optimization (ACOII) algorithm to solve the dynamic facility layout problem for construction sites. The algorithm uses a construction approach in building the layout solutions over time and uses a discrete dynamic search with heuristic info based on both relocation and flow costs to influence facilities’ placement in different time periods. The performance of ACOII is investigated using randomly generated data sets where the number of facilities and the number of time periods in the planning horizon vary to mimic what happens on a construction site over time. The experimental results show that ACOII is effective in solving the problem. A benchmarking study using instances from the literature showed promising results with improved solutions for all instances with very large number of facilities and periods.

Suggested Citation

  • Pierrette P. Zouein & Sarah Kattan, 2022. "An improved construction approach using ant colony optimization for solving the dynamic facility layout problem," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(7), pages 1517-1531, July.
    • Handle: RePEc:taf:tjorxx:v:73:y:2022:i:7:p:1517-1531
    DOI: 10.1080/01605682.2021.1920345
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    Cited by:

    1. Gang Yao & Rui Li & Yang Yang, 2023. "An Improved Multi-Objective Optimization and Decision-Making Method on Construction Sites Layout of Prefabricated Buildings," Sustainability, MDPI, vol. 15(7), pages 1-23, April.

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