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AbouRizk, S (2010) Role of Simulation in Construction Engineering and Management. Journal of Construction Engineering and Management, 136(10), 1140–53.

González, V, Alarcón, L F, Maturana, S, Mundaca, F and Bustamante, J (2010) Improving Planning Reliability and Project Performance Using the Reliable Commitment Model. Journal of Construction Engineering and Management, 136(10), 1129–39.

Hegazy, T and Menesi, W (2010) Critical Path Segments Scheduling Technique. Journal of Construction Engineering and Management, 136(10), 1078–85.

Kheni, N A, Gibb, A G F and Dainty, A R J (2010) Health and Safety Management within Small- and Medium-Sized Enterprises (SMEs) in Developing Countries: Study of Contextual Influences. Journal of Construction Engineering and Management, 136(10), 1104–15.

Leung, M, Chan, Y and Yuen, K (2010) Impacts of Stressors and Stress on the Injury Incidents of Construction Workers in Hong Kong. Journal of Construction Engineering and Management, 136(10), 1093–103.

Powell, R and Copping, A (2010) Sleep Deprivation and Its Consequences in Construction Workers. Journal of Construction Engineering and Management, 136(10), 1086–92.

Shen, Y and Luo, Y Z (2010) Accumulative Sliding Construction Method for Large-Span Latticed Shells. Journal of Construction Engineering and Management, 136(10), 1154–7.

Tan, Y, Shen, L and Langston, C (2010) Contractors’ Competition Strategies in Bidding: Hong Kong Study. Journal of Construction Engineering and Management, 136(10), 1069–77.

Wong, C K, Fung, I W H and Tam, C M (2010) Comparison of Using Mixed-Integer Programming and Genetic Algorithms for Construction Site Facility Layout Planning. Journal of Construction Engineering and Management, 136(10), 1116–28.

  • Type: Journal Article
  • Keywords: Algorithms; Computer programming; Construction sites; Planning; Genetic algorithms; Mixed-integer programming; Facility layout;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000214
  • Abstract:
    The use of modular construction has gained wide acceptance in the industry. For a specific construction facility layout problem such as site precast standardized modular units, it requires the establishment of an on-site precast yard. Arranging the precast facilities within a construction site presents real challenge to site management. This complex task is further augmented with the involvement of several resources and different transport costs. A genetic algorithm (GA) model was developed for the search of a near-optimal layout solution. Another approach using mixed-integer programming (MIP) has been developed to generate optimal facility layout. These two approaches are applied to solve with an example in this paper to demonstrate that the solution quality of MIP outperforms that of GA. Further, another scenario with additional location constraints can also be solved readily by MIP, which, however, if modeled by GA, the solution process would be complicated. The study has highlighted that MIP can perform better than GA in site facility layout problems in which the site facilities and locations can be represented by a set of integer variables.