Optimum planning and scheduling of repetitive construction projects: multi-objective optimization using the cuckoo search algorithm

Construction projects, such as infrastructure systems and housing projects, often involve repetitive tasks, necessitating careful work scheduling to avoid disruptions during execution. Time and cost are two interdependent factors that significantly influence the overall project duration. Shortening the project duration typically leads to increased project costs. Therefore, striking an optimum balance between these two objectives is crucial. In this study, we develop a multi-objective optimization model specifically for planning and scheduling repetitive construction projects. The primary aim of the model is to minimize both the project duration and project cost simultaneously. To achieve this, we employ the Cuckoo search algorithm, which enables us to obtain a set of Pareto-optimal solutions. The Pareto-optimal solutions obtained through our model provide project managers with the flexibility to select the most suitable solution for their specific project requirements. By conducting a quantitative assessment, project managers can make informed decisions based on the available options. To showcase the practical application and validate the efficiency of our model, we conducted a detailed case study. The case study focuses on a real-world construction project, providing a tangible example of how our model can be implemented and assessed in a practical setting. Through this case study, we demonstrate the model's efficacy in optimizing the planning and scheduling of repetitive construction projects.