Hybrid Mean Particle Swarm Optimization Algorithm for Permutation Flow Shop Scheduling Problem

摘要

This paper presents a new hybrid mean particle swarm optimization algorithm with improved NEH heuristic approach and local search strategies by using an immune mechanism. This hybrid mean particle swarm optimization algorithm is used for permutation flow shop scheduling problems. Finally, twenty-five problems are used to test the performance of the algorithm, the experimental results show that the proposed approach is an effective and practical.