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Application of Clonal Selection Algorithm in Construction Site Utilization Planning Optimization

机译:克隆选择算法在施工现场利用规划优化中的应用

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Various algorithms inspired by evolutionary and physical processes have been extensively applied in solving complex construction engineering optimization problems. In this paper, Artificial Immune Systems (AIS), a computational approach inspired by the processes of human immune system, is introduced in terms of its basic mechanisms and its applications in construction engineering. Specifically, Clonal Selection Algorithm (CSA), one of main algorithms that form AIS, is based on clonal selection process of the immune system which includes the selection, hypermutation, and receptor editing processes. We discuss the CSA in detail and present its application in the classic construction optimization problem, construction site utilization planning (CSUP), which is the decision making process for identifying the most optimal layout of temporary facilities designed to support the construction process. When applied to a test case published in research literature, we found that CSA shows a robust capacity to search the solution space effectively and efficiently.
机译:通过进化和物理过程启发的各种算法已经广泛应用于解决复杂的建筑工程优化问题。本文在其基本机制及其在建筑工程中的应用方面,引入了人工免疫系统(AIS),这是一种由人类免疫系统的过程的计算方法。具体地,克隆选择算法(CSA),形成AIS的主要算法之一,基于免疫系统的克隆选择过程,该免疫系统包括选择,超责容和受体编辑过程。我们详细讨论了CSA,并呈现了其在经典建筑优化问题,施工现场利用计划(CSUP)中的应用,这是识别临时设施最佳布局的决策过程,旨在支持施工过程。当应用于在研究文献中发布的测试用例时,我们发现CSA显示了有效且有效地搜索解决方案空间的强大容量。

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