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首页> 外文期刊>Journal of Computing in Civil Engineering >Site Layout and Construction Plan Optimization Using an Integrated Genetic Algorithm Simulation Framework
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Site Layout and Construction Plan Optimization Using an Integrated Genetic Algorithm Simulation Framework

机译:使用集成遗传算法仿真框架的场地布局和施工计划优化

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Efficiency of a planned site layout is essential for the successful completion of construction projects. Despite considerable research undertaken for optimizing construction site layouts, most models developed for this purpose have neglected the mutual impacts of the site layout and construction operation variables and are unable to thoroughly model these impacts. This paper outlines a framework enabling planners to anticipate site layout variables (i.e.,size, location, and orientation of temporary facilities) and construction plan variables (e.g.,resources and material delivery plan), and simultaneously optimize them in an integrated model. In this framework, genetic algorithm (GA) and simulation are integrated; GA heuristically searches for the near-optimum solution with minimum costs by generating feasible candidate solutions, and simulation mimics construction processes and measures the project costs by adopting those candidate solutions. The contribution of this framework is the ability to capture the mutual impacts of site layout and construction plans in a unified simulation model and optimize their variables in GA, which subsequently entails developing a more efficient and realistic plan. Applicability of the framework is presented in a steel erection project. (C) 2017 American Society of Civil Engineers.
机译:计划好的场地布局的效率对于成功完成建设项目至关重要。尽管进行了大量研究以优化建筑工地布局,但为此目的开发的大多数模型却忽略了工地布局和建筑作业变量的相互影响,因此无法彻底模拟这些影响。本文概述了一个框架,使计划人员可以预测场地布局变量(即临时设施的大小,位置和方向)和施工计划变量(例如资源和物料交付计划),并同时在集成模型中对其进行优化。在此框架中,遗传算法(GA)与仿真相结合。 GA会通过生成可行的候选解决方案来试探性地寻找成本最低的接近最佳的解决方案,而模拟则通过采用这些候选解决方案来模拟施工过程并衡量项目成本。该框架的作用是能够在统一的仿真模型中捕获站点布局和施工计划的相互影响,并在GA中优化其变量,从而需要开发更有效,更切合实际的计划。该框架的适用性在钢铁安装项目中有所介绍。 (C)2017年美国土木工程师学会。

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