An Integrated Multi-objective Approach to the Flexible Job-Shop Scheduling Problem using Particle Swarm Optimization

摘要

Flexible job-shop problem is an extension of the job-shop problem that allows an operation to be processed by any machine from a given set along different routes. This paper presents a new approach based on hybridization of the particle swarm and local search algorithm to solve the multi-objective flexible job-shop problem. The particle swarm optimization is an efficient and new evolutionary computation technique inspired by birds' flight. The multi-objective particle swarm algorithm is applied to the flexible job-shop problem based on priority. The results indicate that the proposed algorithm satisfactorily captures the multi-objective flexible job-shop problem and competes well with similar approaches.