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Evaluating flexible solutions in single machine scheduling via objective function maximization: the study of a computational complexity

dc.contributor.authorPortmann, Marie-Claude
dc.contributor.authorKovalyov, Mikhail Y.
dc.contributor.authorAloulou, Mohamed Ali
dc.date.accessioned2009-12-10T09:44:30Z
dc.date.available2009-12-10T09:44:30Z
dc.date.issued2007
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/2650
dc.language.isoenen
dc.subjectSchedulingen
dc.subjectsingle machineen
dc.subjectmaxi- mization problemsen
dc.subject.ddc003en
dc.titleEvaluating flexible solutions in single machine scheduling via objective function maximization: the study of a computational complexityen
dc.typeArticle accepté pour publication ou publié
dc.contributor.editoruniversityotherBelarusian State University Minsk;Biélorussie
dc.contributor.editoruniversityotherINRIA-Lorraine,Nancy;France
dc.description.abstractenWe study a deterministic problem of evaluating the worst case performance of flexible solutions in the single machine scheduling. A flexible solution is a set of schedules following a given structure de- termined by a partial order of jobs and a type of the schedules. In this paper, the schedules of active and non-delay type are considered. A flexible solution can be used on-line to absorb the impact of data disturbances related to, for example, job arrival, tool availability or machine breakdowns. The performance of a flexible solution includes the best case and the worst case performances. The best case perfor- mance is an ideal performance that can be achieved only if the on-line conditions allow to implement the best schedule of the set of schedules characterizing the flexible solution. In contrast, the worst case perfor- mance indicates how poorly the flexible solution may perform when fol- lowing the given structure in the on-line circumstances. The best-case and the worst-case performances are usually evaluated by the minimum and maximum values of the considered objective function, respectively. We present algorithmic and computational complexity results for some maximization scheduling problems. In these problems, the jobs to be scheduled have different release dates and precedence constraints may be given on the set of jobs.en
dc.relation.isversionofjnlnameRAIRO
dc.relation.isversionofjnlvol41en
dc.relation.isversionofjnlissue1en
dc.relation.isversionofjnldate2007
dc.relation.isversionofjnlpages1-18en
dc.relation.isversionofdoihttp://dx.doi.org/10.1051/ro:20070012en
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherEDP Sciencesen
dc.subject.ddclabelRecherche opérationnelleen


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