1 Ocak 2011 Dergi makalesi Açık Erişim

Tarim, S. Armagan; Dogru, Mustafa K.; Oezen, Ulas; Rossi, Roberto

Dublin Core

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  <dc:creator>Tarim, S. Armagan</dc:creator>
  <dc:creator>Dogru, Mustafa K.</dc:creator>
  <dc:creator>Oezen, Ulas</dc:creator>
  <dc:creator>Rossi, Roberto</dc:creator>
  <dc:date>2011-01-01</dc:date>
  <dc:description>We provide an efficient computational approach to solve the mixed integer programming (MIP) model developed by Tarim and Kingsman [8] for solving a stochastic lot-sizing problem with service level constraints under the static-dynamic uncertainty strategy. The effectiveness of the proposed method hinges on three novelties: (i) the proposed relaxation is computationally efficient and provides an optimal solution most of the time, (ii) if the relaxation produces an infeasible solution, then this solution yields a tight lower bound for the optimal cost, and (iii) it can be modified easily to obtain a feasible solution, which yields an upper bound. In case of infeasibility, the relaxation approach is implemented at each node of the search tree in a branch-and-bound procedure to efficiently search for an optimal solution. Extensive numerical tests show that our method dominates the MIP solution approach and can handle real-life size problems in trivial time. (C) 2011 Elsevier B.V. All rights reserved.</dc:description>
  <dc:identifier>https://aperta.ulakbim.gov.trrecord/19405</dc:identifier>
  <dc:identifier>oai:zenodo.org:19405</dc:identifier>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>http://www.opendefinition.org/licenses/cc-by</dc:rights>
  <dc:source>EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 215(3) 563-571</dc:source>
  <dc:title>An efficient computational method for a stochastic dynamic lot-sizing problem under service-level constraints</dc:title>
  <dc:type>info:eu-repo/semantics/article</dc:type>
  <dc:type>publication-article</dc:type>
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