Solving the Multi-Mode Resource Availability Cost Problem in Project Scheduling Based on Modified Particle Swarm Optimization

This paper proposes a model for multi-mode resource availability cost problem (MMRACP) in project scheduling which minimizes the resource availability cost required to finish all activities in a project at a given project deadline. Precedence relations exist among the activities of the project in the model. Furthermore, renewable and nonrenewable resources are both considered. MMRACP is a nondeterministic polynomial time hard (NP-hard) problem, as a result it is very difficult to use an exact method to solve it. For solving MMRACP, we developed a modified particle swarm optimization method combined with path relinking procedure and designed a heuristic algorithm to improve the fitness of the solution. At the end, a computational experiment including 180 instances was designed to test the performance of the modified particle swarm optimization. Comparative computational results show that the modified particle swarm optimization is very effective in solving MMRACP.