Title: Performance improvement of the particle swarm optimisation algorithm for the flexible job shop problem under machines breakdown

Authors: Rim Zarrouk; Imed Eddine Bennour; Jemai Abderrazak

Addresses: Polytechnic School, University of Carthage, Tunisia; Labo NOCCS, National Engineering School of Sousse, University of Sousse, Tunisia ' Labo NOCCS, National Engineering School of Sousse, University of Sousse, Tunisia ' Labo LIP2, Faculty of Sciences of Tunis, University of Tunis El Manar, Tunisia

Abstract: One of the most challenging problems in the manufacturing field is to solve the flexible job shop problem (FJSP) subject to machine breakdowns (caused a loss of time). The meta-heuristic particles swarm optimisation (PSO) is well suited to solve the FJSP but it might be time consuming specially on monocore platforms. In this paper, we propose a set of PSO-FJSP variants that aim to improve the run time of the pre-scheduling step. Then we propose three rescheduling variants to handle machine breakdowns: two variants aim to improve the robustness of the schedule, while the third aims to improve the stability of the schedule. Standard benchmarks are used to evaluate and compare the proposed variants.

Keywords: flexible job shop problem; swarm optimisation; scheduling; performance; machine breakdowns.

DOI: 10.1504/IJIEI.2018.091876

International Journal of Intelligent Engineering Informatics, 2018 Vol.6 No.3/4, pp.396 - 416

Received: 08 Apr 2017
Accepted: 20 Jun 2017
Published online: 20 May 2018 *

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