Constructing a Multi-Objective Optimization Model for Engineering Projects Based on NSGA-II Algorithm under the Background of Green Construction

Fushun Zhang
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Abstract

In the context of Sustainability Development (SD), Green Construction (GC) has become a key direction for optimizing engineering project objectives. In order to improve the management ability of project engineering in GC, an improved NSGA - II algorithm was used in this study to establish a multi-optimization model for engineering projects. In this process, the hill climbing is introduced to improve the search ability of NSGA - Ⅱ algorithm. Finally, a Multi-Objective Optimization (MOP) model with strong convergence and distribution was obtained. In subsequent validation experiments, the total construction period of the engineering project MOP model based on the improved NSGA - II algorithm was between 190 and 234days. The total cost ranges from 171,473 to 20,461,800 yuan. Its total mass ranges from 90.41% to 92.19%. Its total safety is between 91.30% and 99.32%. The total environment is between 144.54 and 193.58. Its total resources range from 86.21% to 99.91%. The cost of improving the NSGA-II algorithm is 500300 yuan lower than that of the NSGA-II algorithm, with a resource target increase of 0.4% and an environmental target increase of 4.33%. The iteration curves of the improved NSGA - II algorithm in terms of duration, cost, and environmental objective function are lower than those of the NSGA - II algorithm. Overall, the improved NSGA - II algorithm has better MOP performance, can obtain better Pareto solutions, and has better performance.
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绿色建筑背景下基于NSGA-II算法的工程项目多目标优化模型构建
在可持续发展(SD)背景下,绿色建筑(GC)已成为优化工程项目目标的关键方向。为了提高GC项目工程的管理能力,本研究采用改进的NSGA - II算法,建立了工程项目的多优化模型。在此过程中,为了提高NSGA -Ⅱ算法的搜索能力,引入了爬坡的方法。最后,得到了一个具有强收敛性和强分布性的多目标优化模型。在随后的验证实验中,基于改进NSGA - II算法的工程项目MOP模型总工期在190 ~ 234天之间。总成本从171473元到20461800元不等。其总质量为90.41% ~ 92.19%。其总安全性在91.30% ~ 99.32%之间。总环境在144.54 ~ 193.58之间。其资源总量为86.21% ~ 99.91%。改进NSGA-II算法的成本比改进NSGA-II算法低500300元,资源目标提高0.4%,环境目标提高4.33%。改进的NSGA - II算法的迭代曲线在持续时间、代价和环境目标函数方面均低于NSGA - II算法。总体而言,改进的NSGA - II算法具有更好的MOP性能,可以获得更好的Pareto解,具有更好的性能。
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来源期刊
Decision Making Applications in Management and Engineering
Decision Making Applications in Management and Engineering Decision Sciences-General Decision Sciences
CiteScore
14.40
自引率
0.00%
发文量
35
审稿时长
14 weeks
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