Advancing equipment management for construction: introducing a new model for cost, time and quality optimization

Purpose This paper aims to improve the selection process of heavy machinery in construction projects by developing an advanced optimization technique using the Improved Particle Swarm Optimization algorithm (IPSOM). The main objectives of such a study are to optimize the key parameters of time and cost while ensuring adherence to a predefined quality benchmarks, thereby facilitating more informed and balanced decision-making in construction management. Design/methodology/approach A rigorous methodology was applied to identify the relevant optimization parameters, combining a comprehensive literature review with consultations with industry experts. This approach identified the most influential factors affecting machinery selection, ensuring the model’s applicability and relevance across different project scales and complexities. Unique to this study, the model’s novelty lies in its advanced application of the IPSOM tailored to the construction industry’s specific needs, offering a systematic approach to balancing time, cost and quality considerations. Findings IPSOM was validated through a detailed case study, which provided empirical evidence of the model’s effectiveness in a real-world application. The study introduces a groundbreaking approach to optimizing equipment selection in highway construction, with the dual aims of minimizing costs and project duration while maintaining high-quality standards. The model proposed in the study saved 53% time, reduced costs by 30.8% and increased quality by 26.3%, outperforming traditional equipment selection methods. Originality/value The case study analysis demonstrated the model’s adaptability and potential as a crucial tool for decision-making in construction projects.