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The Scientific World Journal
Volume 2014 (2014), Article ID 902950, 8 pages
http://dx.doi.org/10.1155/2014/902950
Research Article

A PSO-Based Hybrid Metaheuristic for Permutation Flowshop Scheduling Problems

1School of Information Engineering, Shenyang University, Shenyang 110044, China
2School of Information Science and Technology, Tsinghua University, Beijing 100084, China

Received 4 August 2013; Accepted 5 November 2013; Published 29 January 2014

Academic Editors: S. Berres and W.-C. Lee

Copyright © 2014 Le Zhang and Jinnan Wu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper investigates the permutation flowshop scheduling problem (PFSP) with the objectives of minimizing the makespan and the total flowtime and proposes a hybrid metaheuristic based on the particle swarm optimization (PSO). To enhance the exploration ability of the hybrid metaheuristic, a simulated annealing hybrid with a stochastic variable neighborhood search is incorporated. To improve the search diversification of the hybrid metaheuristic, a solution replacement strategy based on the pathrelinking is presented to replace the particles that have been trapped in local optimum. Computational results on benchmark instances show that the proposed PSO-based hybrid metaheuristic is competitive with other powerful metaheuristics in the literature.