NSGA-III based optimization model for balancing time, cost, and quality in resource-constrained retrofitting projects

Q2 Engineering
Abhishek Arya, G. I. Gunarani, V. Rathinakumar, Apurva Sharma, Aditya Kumar Pati, Krushna Chandra Sethi
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引用次数: 0

Abstract

This paper introduces an innovative resource-constrained time–cost-quality trade-off optimization model (RCTCQ-TOOM) designed specifically for retrofitting planning projects in densely populated areas such as India. The model integrates seven critical aspects of retrofitting and leverages the advanced NSGA-III algorithm to find Pareto-optimal solutions that effectively balance project completion time, cost, and quality constraints. A case of retrofitting project of Gwalior, India, demonstrates the real-world applicability and effectiveness of RCTCQ-TOOM in providing valuable decision support for stakeholders. The study showcases how the model can optimize retrofitting projects by presenting a diverse set of superior-quality solutions along Pareto-optimal front within a reasonable computational timeframe. The paper also includes a comparative analysis with other multi-objective optimization methods, such as Multi-Objective Particle Swarm Optimization (MOPSO), Multi-Objective Ant Colony Optimization (MOACO), and Multi-Objective Teaching–Learning-Based Optimization (MOTLBO). This analysis highlights NSGA-III's superior performance in achieving both convergence and diversity of optimal solutions. The findings indicate that NSGA-III effectively balances time, cost, and quality aspects, making it a robust tool for optimizing retrofitting projects. The RCTCQ-TOOM, combined with the NSGA-III algorithm, promotes sustainability and resilience in urban development by providing a comprehensive and efficient optimization framework.

Graphical abstract

基于 NSGA-III 的优化模型,用于在资源受限的改造项目中平衡时间、成本和质量
本文介绍了一种创新的资源受限时间-成本-质量权衡优化模型(RCTCQ-TOOM),该模型专为印度等人口稠密地区的改造规划项目而设计。该模型综合了改造工程的七个关键方面,并利用先进的 NSGA-III 算法找到帕累托最优解,从而有效平衡项目完工时间、成本和质量约束。印度瓜里奥尔(Gwalior)改造项目的一个案例证明了 RCTCQ-TOOM 在为利益相关者提供有价值的决策支持方面的实际应用性和有效性。该研究展示了该模型如何在合理的计算时间内,沿着帕累托最优前沿提出一系列不同的优质解决方案,从而优化改造项目。论文还包括与其他多目标优化方法的比较分析,如多目标粒子群优化(MOPSO)、多目标蚁群优化(MOACO)和基于教学-学习的多目标优化(MOTLBO)。这项分析凸显了 NSGA-III 在实现最优解的收敛性和多样性方面的卓越性能。研究结果表明,NSGA-III 能有效地平衡时间、成本和质量,是优化改造项目的有力工具。RCTCQ-TOOM 与 NSGA-III 算法相结合,提供了一个全面、高效的优化框架,促进了城市发展的可持续性和复原力。
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来源期刊
Asian Journal of Civil Engineering
Asian Journal of Civil Engineering Engineering-Civil and Structural Engineering
CiteScore
2.70
自引率
0.00%
发文量
121
期刊介绍: The Asian Journal of Civil Engineering (Building and Housing) welcomes articles and research contributions on topics such as:- Structural analysis and design - Earthquake and structural engineering - New building materials and concrete technology - Sustainable building and energy conservation - Housing and planning - Construction management - Optimal design of structuresPlease note that the journal will not accept papers in the area of hydraulic or geotechnical engineering, traffic/transportation or road making engineering, and on materials relevant to non-structural buildings, e.g. materials for road making and asphalt.  Although the journal will publish authoritative papers on theoretical and experimental research works and advanced applications, it may also feature, when appropriate:  a) tutorial survey type papers reviewing some fields of civil engineering; b) short communications and research notes; c) book reviews and conference announcements.
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