基于资源波动矩变化的超大型建筑改造资源利用遗传算法优化

Pornpote Nusen, Pratch Piyawongwisal, Sunita Nusen, M. Kaewmoracharoen
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引用次数: 0

摘要

本文比较了基于资源波动矩(Mx)变化的遗传算法(GA)在特大型建筑改造中的资源优化利用。Mx变量由day squared上的资源需求决定,对多目标优化的结果有很大影响。在本研究中,提出了一种基于x的资源利用优化模型,该模型针对5个变量进行优化。此外,该方法具有灵活性,施工规划者可以指定可选施工顺序的前任或偏好,从而获得更有效的最优调度。考虑了Mx的三个激活函数,分别是Mx和Mx /1000。在这项工作中,所考虑的模型被应用于大学主图书馆建筑改造项目的实际数据,该项目包括251项活动。将承包商的工作计划作为优化过程的初始调度。对比三种模型的实验结果可以看出,在特大型建筑改造中,形式和Mx/1000更适合采用遗传算法优化资源利用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Resource Utilization Optimization using Genetic Algorithm based on Variation of Resource Fluctuation Moment for Extra-Large Building Renovation
This paper compared optimizing resource utilization using Genetic Algorithm (GA) based on variation of resource fluctuation moment (Mx) for extra-large building renovation. The Mx variable, as determined by resource demand on day squared, has a large effect on the result of multi-objective optimization. In this research, an Mx-based optimization model targeting five variables for resource utilization was proposed. In addition, the proposed method is flexible in that the construction planners could specify predecessors or preferences for optional construction sequences so that a more efficient optimal scheduling may be obtained. Three activation functions for Mx were considered, namely Mx, and Mx /1000. In this work, the models in consideration were applied to real data from the university main library building renovation projects which consisted of 251 activities. The contractor's work plan was used as the initial scheduling for the optimization process. When comparing the experimental results from all 3 models, it can be seen that the form and Mx/1000 are more suitable in optimizing resource utilization through GA method in extra-large building renovation.
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