A hybrid multi-verse optimization for the fuzzy flexible job-shop scheduling problem. (January 2019)

• Record Type: Journal Article
• Authors: Lin, Jian; Zhu, Lei; Wang, Zhou-Jing
• Is Part Of: Computers & industrial engineering. Volume 127(2019)
• Page Start: 1089
• Page End: 1100
• Publication Date: 2019-01
• Subjects: Multi-verse optimization -- Fuzzy flexible job-shop scheduling -- Hybrid algorithm; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2018.11.046
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: The MVO algorithm is deeply studied by integrating several novel local search heuristics. A hybrid algorithm called HMVO is proposed for solving the FFJSP. The performance of the HMVO is evaluated by using three benchmark sets. New best solutions are obtained by the proposed hybrid scheme. Abstract: In this paper, a novel algorithm called hybrid multi-verse optimization (HMVO) is proposed to address the fuzzy flexible job-shop scheduling problem (FFJSP). Firstly, path relinking technique is introduced to mimic the process of swapping objects through the black/white holes. Secondly, a mixed phase which integrates insertion-based heuristic and path relinking technique is incorporated into the algorithm to enlarge the search space. Thirdly, pairwise-based local search is proposed as a hybrid strategy to improve the solution quality. Finally, extensive experiments are conducted on three benchmark sets to investigate the performance of the proposed HMVO. Computational results and comparisons with some existing meta-heuristics demonstrate the competitive efficiency and effectiveness of the proposed algorithm.