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

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