Flexible job-shop scheduling problem with sequence-dependent setup times using genetic algorithm

Informations générales

Année de publication

2016

Type

Conférence

Description

International Conference on Enterprise Information Systems. Vol. 3. SCITEPRESS, 2016.

Résumé

Job shop scheduling problems (JSSP) are among the most intensive combinatorial problems studied in literature. The flexible job shop problem (FJSP) is a generalization of the classical JSSP where each operation can be processed by more than one resource. The FJSP problems cover two difficulties, namely, machine assignment problem and operation sequencing problem. This paper investigates the flexible job-shop scheduling problem with sequence-dependent setup times to minimize two kinds of objectives function: makespan and bi-criteria objective function. For that, we propose a genetic algorithm (GA) to solve this problem. To evaluate the performance of our algorithm, we compare our results with other methods existing in literature. All the results show the superiority of our GA against the available ones in terms of solution quality.

BibTeX
@conference{iceis16,
author={Ameni Azzouz and Meriem Ennigrou and Lamjed Ben Said},
title={Flexible Job-shop Scheduling Problem with Sequence-dependent Setup Times using Genetic Algorithm},
booktitle={Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2016},
pages={47-53},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005821900470053},
isbn={978-989-758-187-8},
}