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The application of the ant colony optimization algorithm to the construction site layout planning problem

Author

Listed:
  • Ka-Chi Lam
  • Xin Ning
  • Thomas Ng

Abstract

A good site layout is vital to ensure the safety of the working environment, and for effective and efficient operations. Moreover, it minimizes travel distance, decreases materials handling, and avoids the obstruction of materials and plant movement. Based on studies in the manufacturing industry, the cost of materials handling could be reduced by 20-60% if an appropriate facility layout is adopted. In designing a site layout, a planner will first position the key facilities that influence the method and sequence of construction, and then assign the remaining facilities in the available space that is left over. This process is similar to the positioning of facilities in the ant colony optimization (ACO) algorithm. The general principle of the ACO algorithm is to assign facilities to a location one by one, and the occupied locations are deleted from the location scope in the next assignment. In the study, ACO algorithm is employed to resolve the construction site layout planning problem in a hypothetical medium-sized construction project. By applying fuzzy reasoning and the entropy technique, the study calculates the closeness relationship between facilities, in which the optimal site layout is affected by the mutual interaction of facilities.

Suggested Citation

  • Ka-Chi Lam & Xin Ning & Thomas Ng, 2007. "The application of the ant colony optimization algorithm to the construction site layout planning problem," Construction Management and Economics, Taylor & Francis Journals, vol. 25(4), pages 359-374.
    • Handle: RePEc:taf:conmgt:v:25:y:2007:i:4:p:359-374
    DOI: 10.1080/01446190600972870
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    Cited by:

    1. Cynthia Changxin Wang & Samad M.E. Sepasgozar & Mudan Wang & Jun Sun & Xin Ning, 2019. "Green Performance Evaluation System for Energy-Efficiency-Based Planning for Construction Site Layout," Energies, MDPI, vol. 12(24), pages 1-21, December.
    2. Farmakis Panagiotis M. & Chassiakos Athanasios P., 2018. "Genetic algorithm optimization for dynamic construction site layout planning," Organization, Technology and Management in Construction, Sciendo, vol. 10(1), pages 1655-1664, February.

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