A Memetic Algorithm with Particle Swarm Optimization and Differential Evolution Algorithm to Rescheduling Problem in Multi-Agent System

Dynamic rescheduling model and its solution method are of significant importance for the dynamic scheduling problem in manufacturing system. However, few attempts have been done on the universal communication and negotiation mechanism for the dynamic rescheduling problem and corresponding solution approach. A dynamic rescheduling model, which is based on Multi-Agent System (MAS), was proposed. A memetic algorithm with PSO (particle swarm optimization) and DE (differential evolution) was presented as the solution method to the rescheduling model. Furthermore, the simulation results in dynamic scheduling accompanying with its perturbation show that the proposed model and the algorithm are effective to the dynamic scheduling problem in manufacturing system.