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Comparison of Using Mixed-Integer Programming and Genetic Algorithms for Construction Site Facility Layout Planning

机译:混合整数规划与遗传算法在施工现场设施布局规划中的比较

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摘要

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.
机译:模块化结构的使用已在业界获得广泛认可。对于特定的建筑设施布局问题,例如现场预制标准化模块化单元,需要建立现场预制场。在建筑工地内布置预制设施对工地管理提出了真正的挑战。涉及多种资源和不同的运输成本,进一步增加了这项复杂的任务。开发了一种遗传算法(GA)模型,用于寻找接近最佳的布局解决方案。已经开发出另一种使用混合整数编程(MIP)的方法来生成最佳设施布局。本文以这两种方法为例进行说明,以证明MIP的解决方案质量优于GA。此外,还可以通过MIP轻松解决具有附加位置限制的另一种情况,但是,如果使用GA进行建模,则解决过程将会很复杂。该研究强调,在站点设施布局问题中,MIP可以比GA更好,在站点问题中,站点设施和位置可以由一组整数变量表示。

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