Metaheuristic Multi-Objective Optimization Approach for Repetitive Construction Project Scheduling

The optimization of schedules for repetitive projects is a crucial phase in establishing an effective project timeline concerning both duration and cost. This study presents an innovative metaheuristic multi-objective optimization model tailored for repetitive projects. Distinguished by its original features, this model empowers schedulers to identify an optimal schedule that concurrently minimizes project duration, total cost, and interruption time. It encompasses various constraints and factors, including learning and forgetting effects, inter-activity soft logic, limited work interruption allowances, multiple crew formations, multiple construction methods per activity, while retaining all Critical Path Method (CPM) scheduling capabilities. The effectiveness of this new approach was validated through application to two case studies, demonstrating its capability to deliver optimal schedules for repetitive projects with heightened accuracy in minimizing project duration, cost, and interruption. Furthermore, the integration of learning effects, soft logic, and work interruption allowances within the optimization process substantially reduced project duration and cost, thereby yielding more precise and dependable optimal solutions.