Heuristic, optimal, static, and dynamic schedules when processing times are uncertain / Stephen R. Lawrence in Journal of operations management, Vol. 15 N°1 (Fevrier 1997)  

Public ISBD [article]  inJournal of operations management > Vol. 15 N°1 (Fevrier 1997) . - pp. 71–82 Titre : Heuristic, optimal, static, and dynamic schedules when processing times are uncertain Type de document : texte imprimé Auteurs : Stephen R. Lawrence, Auteur ; Edward C. Sewell, Auteur Année de publication : 2007 Article en page(s) : pp. 71–82 Note générale : Génie Industriel Langues : Anglais (eng) Mots-clés : Scheduling Job shop Measurement and methodology Résumé : In this paper we compare the static and dynamic application of heuristic and optimal solution methods to job-shop scheduling problems when processing times are uncertain. Recently developed optimizing algorithms and several heuristics are used to evaluate 53 standard job-shop scheduling problems with a makespan objective when job processing times are known with varying degrees of uncertainty. Results indicate that fixed optimal sequences derived from deterministic assumptions quickly deteriorate with the introduction of processing time uncertainty when compared with dynamically updated heuristic schedules. As processing time uncertainty grows, we demonstrate that simple dispatch heuristics provide performance comparable or superior to that of algorithmically more sophisticated scheduling policies. DEWEY : 658.57 ISSN : 0272-6963 En ligne : http://www.sciencedirect.com/science/article/pii/S0272696396000903 [article] Heuristic, optimal, static, and dynamic schedules when processing times are uncertain [texte imprimé] / Stephen R. Lawrence, Auteur ; Edward C. Sewell, Auteur . - 2007 . - pp. 71–82. Génie Industriel Langues : Anglais (eng) in Journal of operations management > Vol. 15 N°1 (Fevrier 1997) . - pp. 71–82 Mots-clés : Scheduling Job shop Measurement and methodology Résumé : In this paper we compare the static and dynamic application of heuristic and optimal solution methods to job-shop scheduling problems when processing times are uncertain. Recently developed optimizing algorithms and several heuristics are used to evaluate 53 standard job-shop scheduling problems with a makespan objective when job processing times are known with varying degrees of uncertainty. Results indicate that fixed optimal sequences derived from deterministic assumptions quickly deteriorate with the introduction of processing time uncertainty when compared with dynamically updated heuristic schedules. As processing time uncertainty grows, we demonstrate that simple dispatch heuristics provide performance comparable or superior to that of algorithmically more sophisticated scheduling policies. DEWEY : 658.57 ISSN : 0272-6963 En ligne : http://www.sciencedirect.com/science/article/pii/S0272696396000903

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