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

Xiuli Wu and Shaomin Wu ()
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Xiuli Wu: University of Science and Technology Beijing
Shaomin Wu: University of Kent

Journal of Intelligent Manufacturing, 2017, vol. 28, issue 6, No 13, 1457 pages

Abstract: Abstract 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 atomic nucleuses. 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.

Keywords: Flexible job shop scheduling problem; Quantum-inspired evolutionary algorithm; Convergence speed; Local search (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s10845-015-1060-6

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