Skip to Main content Skip to Navigation
Journal articles

Coupling a genetic algorithm with the distributed arrival-time control for the JIT dynamic scheduling of flexible job-shops

Abstract : In order to increase customer satisfaction and competitiveness, manufacturing systems need to combine flexibility with Just-in-Time (JIT) production. Until now, research on JIT scheduling problems has been mostly limited to high volume assembly lines rather than job-shop-like systems, due to their combinatorial complexity. In this paper, we propose a generic strategy for dynamically controlling task schedules by coupling genetic algorithms and distributed arrival-time control to optimise JIT performance. We explore two such hybrid approaches: a sequential approach where the two algorithms work separately and an integrated approach where the distributed arrival time control is embedded into the genetic algorithm. Performance of these approaches is benchmarked with quadratic linear programme solutions to get a gauge of their relative strengths in a static environment. Results from applying these approaches to a job-shop-like automated cell verify their effectiveness for JIT manufacturing under realistic dynamically changing environment.
Document type :
Journal articles
Complete list of metadata

https://hal-uphf.archives-ouvertes.fr/hal-03649136
Contributor : Julie Cagniard Connect in order to contact the contributor
Submitted on : Friday, April 22, 2022 - 11:34:46 AM
Last modification on : Saturday, April 23, 2022 - 3:33:20 AM

Identifiers

Collections

Citation

Gabriel Zambrano Rey, Abdelghani Bekrar, Vittaldas V. Prabhu, Damien Trentesaux. Coupling a genetic algorithm with the distributed arrival-time control for the JIT dynamic scheduling of flexible job-shops. International Journal of Production Research, Taylor & Francis, 2013, 52 (12), pp.3688-3709. ⟨10.1080/00207543.2014.881575⟩. ⟨hal-03649136⟩

Share

Metrics

Record views

9