A Particle Swarm Optimization Algorithm with Crossover for Resource Constrained Project Scheduling Problem

Resource and project optimization scheduling has become the key of the success of researching project in the enterprises. In order to solve the mass resource constrained project scheduling problem, in this paper, an improved particle swarm algorithm (PSO) called particle swarm algorithm with crossover (CPSO) was presented. This improved algorithm is based on PSO and genetic algorithm (GA). Through comparing with SPSO and GA on RCPSP, it is indicated that CPSO not only avoids premature convergence to a high degree, but also keeps a faster convergence rate than SPSO and GA.