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An elitist quantum-inspired evolutionary algorithm for the flexible job-shop scheduling problem

Wu, Xiuli, Wu, Shaomin (2017) An elitist quantum-inspired evolutionary algorithm for the flexible job-shop scheduling problem. Journal of Intelligent Manufacturing, 28 (6). pp. 1441-1457. ISSN 0956-5515. E-ISSN 1572-8145. (doi:10.1007/s10845-015-1060-6) (KAR id:47337)


The flexible job shop scheduling problem (FJSP) is vital to manufacturers especially in today’s constantly changing environment. It is a strongly NP-hard problem and therefore metaheuristics or heuristics are usually pursued to solve it. Most of the existing metaheuristics and heuristics, however, have low efficiency in convergence speed. To overcome this drawback, this paper develops an elitist quantum-inspired evolutionary algorithm. The algorithm aims to minimise the maximum completion time (makespan). It performs a global search with the quantum-inspired evolutionary algorithm and a local search with a method that is inspired by the motion mechanism of the electrons around an atomic nucleus. Three novel algorithms are proposed and their effect on the whole search is discussed. The elitist strategy is adopted to prevent the optimal solution from being destroyed during the evolutionary process. The results show that the proposed algorithm outperforms the best-known algorithms for FJSPs on most of the FJSP benchmarks.

Item Type: Article
DOI/Identification number: 10.1007/s10845-015-1060-6
Uncontrolled keywords: Flexible job shop scheduling problem, Quantum-inspired evolutionary algorithm, Convergence speed, local search
Subjects: H Social Sciences > HA Statistics > HA33 Management Science
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Shaomin Wu
Date Deposited: 24 Feb 2015 10:12 UTC
Last Modified: 09 Dec 2022 01:45 UTC
Resource URI: (The current URI for this page, for reference purposes)

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