Advanced metaheuristic optimization for reducing time and cost while enhancing quality in major projects

DOI registering

Abstract

The management of large and complex construction projects, particularly the optimization of project completion time, cost, quality, and coordinated resource allocation, remains a critical challenge. This challenge becomes increasingly pronounced in projects characterized by numerous activities, strong temporal dependencies, and limited resources. The growing number of concurrent projects has intensified implementation delays, leading to increased construction costs, reduced quality, and, in extreme cases, economic infeasibility. This study proposes an efficient hybrid framework to investigate the factors influencing delay time, project cost, and quality. The results of reliability analysis showed a Cronbach’s alpha value of 0,80 for the design and engineering phase (10 factors), 0,76 for the procurement phase (15 factors), and 0,59 for the construction phase (23 factors), confirming acceptable data reliability. A comparative analysis between the quantitative index method and a metaheuristic approach, namely an enhanced harmony search (HS) algorithm, was then conducted. The results demonstrate that the HS algorithm effectively balances the time-cost-quality trade-off, achieving notable reductions in project duration and total cost while maintaining the desired quality level. The proposed framework exhibits higher convergence stability and adaptability than conventional methods, highlighting its potential as a practical decision-support tool for data-driven and sustainable management of large-scale construction projects.