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dc.contributor.authorChung, Chia-Shin
dc.contributor.authorFlynn, James
dc.contributor.authorRom, Walter
dc.contributor.authorStaliński, Piotr
dc.date.accessioned2018-01-22T16:46:39Z
dc.date.available2018-01-22T16:46:39Z
dc.date.issued2012
dc.identifier.citationChung, Ch., Flynn, J., Walter, R., Staliński, P., A Genetic Algorithm to Minimize the Total Tardiness for M-Machine Permutation Flowshop Problems. Journal of Entrepreneurship, Management and Innovation (JEMI), 2012, vol. 8, nr 2 : Contemporary Management Concepts. Ed. by P. Staliński, s. 26-43en
dc.identifier.issn2299-7326
dc.identifier.urihttps://depot.ceon.pl/handle/123456789/14247
dc.description.abstractThe m-machine, n-job, permutation flowshop problem with the total tardiness objective is a common scheduling problem, known to be NP-hard. Branch and bound, the usual approach to finding an optimal solution, experiences difficulty when n exceeds 20. Here, we develop a genetic algorithm, GA, which can handle problems with larger n. We also undertake a numerical study comparing GA with an optimal branch and bound algorithm, and various heuristic algorithms including the well known NEH algorithm and a local search heuristic LH. Extensive computational experiments indicate that LH is an effective heuristic and GA can produce noticeable improvements over LH.en
dc.language.isoen
dc.publisherWyższa Szkoła Biznesu - National Louis Univeristyen
dc.rightsUznanie autorstwa-Użycie niekomercyjne-Na tych samych warunkach 3.0 Polska*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/pl/*
dc.subjectgenetic algorithmen
dc.subjectschedulingen
dc.subjectpermutation flowshopen
dc.subjecttardinessen
dc.titleA Genetic Algorithm to Minimize the Total Tardiness for M-Machine Permutation Flowshop Problemspl
dc.typearticleen


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Uznanie autorstwa-Użycie niekomercyjne-Na tych samych warunkach 3.0 Polska
Except where otherwise noted, this item's license is described as Uznanie autorstwa-Użycie niekomercyjne-Na tych samych warunkach 3.0 Polska