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Application of the entropy technique and genetic algorithms to construction site layout planning of medium-size projects

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  • K. C. Lam
  • C. M. Tang
  • W. C. Lee

Abstract

Genetic algorithms (GAs) have been introduced into site layout planning as reported in a number of studies. In these studies, the objective functions were defined so as to employ the GAs in searching for the optimal site layout. However, few studies have been carried out to investigate the actual closeness of relationships between site facilities; it is these relationships that ultimately govern the site layout. This study has determined that the underlying factors of site layout planning for medium-size projects include work flow, personnel flow, safety and environment, and personal preferences. By finding the weightings on these factors and the corresponding closeness indices between each facility, a closeness relationship has been deduced. Two contemporary mathematical approaches - fuzzy logic theory and an entropy measure - were adopted in finding these results in order to minimize the uncertainty and vagueness of the collected data and improve the quality of the information. GAs were then applied to searching for the optimal site layout in a medium-size government project using the GeneHunter software. The objective function involved minimizing the total travel distance. An optimal layout was obtained within a short time. This reveals that the application of GA to site layout planning is highly promising and efficient.

Suggested Citation

  • K. C. Lam & C. M. Tang & W. C. Lee, 2005. "Application of the entropy technique and genetic algorithms to construction site layout planning of medium-size projects," Construction Management and Economics, Taylor & Francis Journals, vol. 23(2), pages 127-145.
    • Handle: RePEc:taf:conmgt:v:23:y:2005:i:2:p:127-145
    DOI: 10.1080/0144619042000202834
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    References listed on IDEAS

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    1. Zhaoxia Li & Michael Anson & Guangming Li, 2001. "A procedure for quantitatively evaluating site layout alternatives," Construction Management and Economics, Taylor & Francis Journals, vol. 19(5), pages 459-467.
    2. C. M. Tam & Thomas Tong, 2003. "GA-ANN model for optimizing the locations of tower crane and supply points for high-rise public housing construction," Construction Management and Economics, Taylor & Francis Journals, vol. 21(3), pages 257-266.
    3. Emad Elbeltagi & Tarek Hegazy & Abdel Hady Hosny & Adel Eldosouky, 2001. "Schedule-dependent evolution of site layout planning," Construction Management and Economics, Taylor & Francis Journals, vol. 19(7), pages 689-697.
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