[article]
Titre : |
Worst-case analysis for flow shop scheduling problems with an exponential learning effect |
Type de document : |
texte imprimé |
Auteurs : |
Wang, J.-B., Auteur ; M.-Z. Wang, Auteur |
Année de publication : |
2012 |
Article en page(s) : |
pp. 130–137 |
Note générale : |
Recherche opérationnelle |
Langues : |
Anglais (eng) |
Mots-clés : |
Scheduling Flow shop Learning effect Worst-case analysis |
Index. décimale : |
001.424 |
Résumé : |
A real industrial production phenomenon, referred to as learning effects, has drawn increasing attention. However, most research on this issue considers only single machine problems. Motivated by this limitation, this paper considers flow shop scheduling problems with an exponential learning effect. By the exponential learning effect, we mean that the processing time of a job is defined by an exponent function of its position in a processing permutation. The objective is to minimize one of the four regular performance criteria, namely, the total completion time, the total weighted completion time, the discounted total weighted completion time, and the sum of the quadratic job completion times. We present heuristic algorithms by using the optimal permutations for the corresponding single-machine scheduling problems. We also analyse the worst-case bound of our heuristic algorithms. |
DEWEY : |
001.424 |
ISSN : |
0160-5682 |
En ligne : |
http://www.palgrave-journals.com/jors/journal/v63/n1/abs/jors201140a.html |
in Journal of the operational research society (JORS) > Vol. 63 N° 1 (Janvier 2012) . - pp. 130–137
[article] Worst-case analysis for flow shop scheduling problems with an exponential learning effect [texte imprimé] / Wang, J.-B., Auteur ; M.-Z. Wang, Auteur . - 2012 . - pp. 130–137. Recherche opérationnelle Langues : Anglais ( eng) in Journal of the operational research society (JORS) > Vol. 63 N° 1 (Janvier 2012) . - pp. 130–137
Mots-clés : |
Scheduling Flow shop Learning effect Worst-case analysis |
Index. décimale : |
001.424 |
Résumé : |
A real industrial production phenomenon, referred to as learning effects, has drawn increasing attention. However, most research on this issue considers only single machine problems. Motivated by this limitation, this paper considers flow shop scheduling problems with an exponential learning effect. By the exponential learning effect, we mean that the processing time of a job is defined by an exponent function of its position in a processing permutation. The objective is to minimize one of the four regular performance criteria, namely, the total completion time, the total weighted completion time, the discounted total weighted completion time, and the sum of the quadratic job completion times. We present heuristic algorithms by using the optimal permutations for the corresponding single-machine scheduling problems. We also analyse the worst-case bound of our heuristic algorithms. |
DEWEY : |
001.424 |
ISSN : |
0160-5682 |
En ligne : |
http://www.palgrave-journals.com/jors/journal/v63/n1/abs/jors201140a.html |
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