Optimizing multi-objective construction management for resource-constrained project scheduling problems: a bio-inspired approach

The optimization challenge of the multi-mode resource-constrained project scheduling problem (MRCPSP) involves balancing both project makespan (Cmax) and net present value (NPV). In this research, we propose utilizing the Multi-objective Artificial Hummingbird Algorithm (MOAHA) for multi-objective optimization in handling the MRCPSP. This algorithm aims to minimize project makespan while maximizing net present value. By applying this approach, we identify the Pareto optimal solution set for the given problem. To assess the effectiveness of the MOAHA on two payment models, namely Payments of Activities (PAC) and Equal Time Interval (ETI), we conduct evaluations using practical construction case studies. These evaluations help determine the efficacy of the MOAHA in addressing challenges related to net present value and makespan within the context of the MRCPSP, considering problems of varying sizes sourced from the Project Scheduling Problem Library (PSPLIB).