Effectiveness of Discrete Particle Swarm Optimization and Binary Differential Evolution for Process Formation

The advantage of flexible structure makes it possible for reconfigurable manufacturing systems (RMS) to respond to business opportunities. One important issue is to form production process in RMS to meet the demand based on available resources. To form a process, it is required to assign manufacturing resources to carry out the operations in it efficiently. The decision problem is to find a configuration using the available resources. Recently, Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms have been developed to optimize processes. In this paper, another two mutation strategies are developed for binary DE. Performance of these algorithms to form production processes will be compared.