Modified Chaotic Particle Swarm Optimization Algorithm for Flexible Process Planning

Abstract

The paper presents an approach based on the application of the Particle Swarm Intelligence algorithm for solving the combinatorial optimization problem of determining the order of execution of operations when processing parts on machines. The proposed approach considers the following types of flexibility: machine flexibility, tool flexibility, process flexibility, and operation sequence flexibility. To represent the flexibility of the machining process of part processing, the method of representing the manufacturing process through networks was chosen, while for the described mathematical model, the criteria for optimization are minimum production time and minimum costs. Experimental results show that the presented algorithm is more efficient, i.e. to give optimal orders of operations in less time and fewer iterations compared to single GA, SA and hybrid GA-SA algorithm.