A simulation-based approach to optimizing resource allocation and logistics in construction projects: a case study

PurposeThis research aims to address the challenge of inefficient decision-making in site layout planning and resource allocation for construction projects. Existing approaches often rely on mathematical models that produce unrealistic results or encounter limitations confined to the site itself. To overcome these constraints, this study proposes a simulation-based approach with a focus on automatically optimizing tower crane placement, depot locations, and supplier selection. The primary objective is to minimize project costs while enhancing overall efficiency and productivity.Design/methodology/approachThe implementation integrates a genetic algorithm and a discrete event simulation model featuring a central control kernel. Key considerations include project boundaries, site layout features, depot locations, and manufacturing and transportation capabilities. The simulation process assesses each solution, encompassing critical stages like manufacturing, transfer to depot, site transportation, and installation. The proposed approach is tested using an actual steel structure project in Tehran, Iran.FindingsResults demonstrate substantial cost reductions compared to the contractor plan, showcasing the superiority of the proposed simulation-based optimization approach. The findings underscore the practical applicability of the research, providing valuable insights for industry professionals to make informed decisions and enhance project outcomes in real-world construction projects.Originality/valueThis integrated simulation-based optimization approach offers a robust framework for realistic and effective site layout planning and resource allocation in general steel construction projects. Its general simulation mechanism allows for easy expansion and application to similar projects, capable of assessing a large number of alternatives. The research contributes to the field by presenting a novel and effective method for addressing decision-making challenges in construction project planning and resource allocation.