Radius particle swarm optimization for resource constrained project scheduling problem

Abstract

The Resource-Constrained Project Scheduling Problem (RCPSP) is a classical well-known and NP-hard problem which includes the resource and precedence constraints that has been applied to many applications. This paper proposes the Radius Particle Swarm Optimization (RPSO) to solve the RCPSP. It extends the Particle Swarm Optimization (PSO) by regrouping the agent particles within the appropriate radius of the circle. It initializes the group of particles, calculate the fitness function, and find the best particle in that group. It is then applied to the RCPSP to find the best scheduling. The proposed method is tested against the PSPLIB standard datasets. The results show that the R-PSO gives better average makespan and standard deviation than traditional PSO.