Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities. (29th April 2014)

• Record Type: Journal Article
• Authors: Li, Jun-qing; Pan, Quan-ke; Mao, Kun
• Other Names: Agarwal P. Academic Editor.; Bhatnagar V. Academic Editor.; Zhang Y. Academic Editor.
• Is Part Of: TheScientificWorldjournal. Volume 2014(2014)
• Publication Date: 2014-04-29
• Subjects: Science -- Periodicals; Technology -- Periodicals; Medicine -- Periodicals; 505
• DOI: 10.1155/2014/596850
• Languages: English
• ISSNs: 2356-6140

Abstract

Abstract : A hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron's benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm.