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• W2954566442 abstract "Purpose The construction industry is characterized by a long construction period, high cost and many uncontrollable factors. The owners and contractors are increasingly focusing on the efficiency of their construction and costs in pursuit of greater economic benefits. However, current methods used in the construction period and cost optimization analysis with multiple constraints the have their own limitations. Therefore, this study aims to propose a combination of genetic algorithm (GA) and building information modeling (BIM) to construct a five-dimensional construction duration-cost optimization model with the advantages of optimization and simulation for optimization. Design/methodology/approach This design first analyzed the characteristics of changing construction period and cost and then improved the genetic mechanism and the data processing method in the GA according to the aforementioned characteristics. Then, BIM technology was combined with GA to testify the feasibility of the model in the practical engineering project. Findings The result proved that this new method was reasonable and effective in dealing with the complicated problem of period and cost. GA accelerated the optimization process and yielded a reliable Pareto solution. BIM technology simulated the construction process before construction to increase the feasibility of the construction scheme. Originality/value This method not only can rapidly provide the best construction period/cost decision to the architect according to the previous working period/cost or contract data that can meet the demands of the architect but also visualize the construction and give a dynamic schedule of the project." @default.
• W2954566442 created "2019-07-12" @default.
• W2954566442 creator A5032546206 @default.
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• W2954566442 date "2019-08-10" @default.
• W2954566442 modified "2023-10-15" @default.
• W2954566442 title "Construction of a 5D duration and cost optimisation model based on genetic algorithm and BIM" @default.
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• W2954566442 doi "https://doi.org/10.1108/jedt-12-2018-0214" @default.
• W2954566442 hasPublicationYear "2019" @default.
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