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• W2022173341 startingPage "1116" @default.
• W2022173341 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." @default.
• W2022173341 created "2016-06-24" @default.
• W2022173341 creator A5042559717 @default.
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• W2022173341 date "2010-10-01" @default.
• W2022173341 modified "2023-10-01" @default.
• W2022173341 title "Comparison of Using Mixed-Integer Programming and Genetic Algorithms for Construction Site Facility Layout Planning" @default.
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• W2022173341 doi "https://doi.org/10.1061/(asce)co.1943-7862.0000214" @default.
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