Integrating quality in resource-constrained time-cost trade-off optimization for civil construction projects using NSGA-III technique

Abstract

In the realm of civil construction projects, achieving an optimal balance between project time, cost, and quality is paramount for ensuring project success and stakeholder satisfaction. Traditional optimization approaches often focus solely on time and cost, potentially neglecting the critical aspect of quality. This study presents a novel framework aimed at integrating quality considerations into resource-constrained time-cost trade-off optimization process using Non-dominated Sorting Genetic Algorithm III (NSGA III) technique. The proposed framework addresses the inherent trade-offs among time, cost, and quality by simultaneously optimizing these objectives. By leveraging NSGA-III, a powerful multi-objective optimization algorithm, the framework generates a set of Pareto-optimal solutions that represent various trade-off options. This enables decision-makers to explore and select solutions that best align with project objectives and constraints. Through solving a real case study project, the effectiveness of the proposed framework is demonstrated in real-world civil construction projects. Results of the study indicate that integrating quality considerations into the time-cost trade-off optimization process leads to more informed decision-making, ultimately enhancing project outcomes and stakeholder satisfaction. This research contributes to advancing the field of project management in civil construction by providing a systematic approach for addressing the complex interplay of time, cost, and quality objectives.