An effective modified Particle Swarm Optimization algorithm for process planning

In the modern manufacturing system, most jobs have a large number of flexible process plans. However, there is only one process plan can be selected for a job in the manufacturing process. Therefore, flexible process plans selection has become a crucial problem in a manufacturing environment. It is a combinatorial optimization problem to conduct operations selection and operations sequencing simultaneously with various constraints deriving from the practical workshop environment as well as the jobs to be processed. In this paper, a new method using a modified particle swarm optimization (PSO) algorithm is presented to optimize the process planning problem. To improve the optimization performance of the approach, efficient encoding and updating strategies have been developed. To verify the feasibility and performance of the proposed approach, a case study has been conducted. The results show that the proposed modified PSO algorithm can generate satisfactory solutions.