Please use this identifier to cite or link to this item: https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1081
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dc.contributor.authorKodaganallur, Viswanathan
dc.contributor.authorSen, Anup Kumar
dc.contributor.authorMitra, Subrata
dc.date.accessioned2021-08-26T06:03:25Z-
dc.date.available2021-08-26T06:03:25Z-
dc.date.issued2014
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84888352558&doi=10.1016%2fj.cie.2013.10.005&partnerID=40&md5=b56ae15208d06f1a26d10b05b3afeff2
dc.identifier.urihttps://ir.iimcal.ac.in:8443/jspui/handle/123456789/1081-
dc.descriptionKodaganallur, Viswanathan, Seton Hall University, 400 South Orange Avenue, NJ 07079, United States; Sen, Anup Kumar, Indian Institute of Management Calcutta, D.H. Road, Joka, Kolkata 700104, India; Mitra, Subrata, Indian Institute of Management Calcutta, D.H. Road, Joka, Kolkata 700104, India
dc.descriptionISSN/ISBN - 03608352
dc.descriptionpp.10-19
dc.descriptionDOI - 10.1016/j.cie.2013.10.005
dc.description.abstractIn this paper, we consider the single machine scheduling problem with quadratic penalties and sequence-dependent (QPSD) setup times. QPSD is known to be NP-Hard. Only a few exact approaches, and to the best of our knowledge, no approximate approaches, have been reported in the literature so far. This paper discusses exact and approximate approaches for solving the problem, and presents empirical findings. We make use of a graph search algorithm, Memory-Based Depth-First Branch-and-Bound (MDFBB), and present an algorithm, QPSD-MDFBB that can optimally solve QPSD, and advances the state of the art for finding exact solutions. For finding approximate solutions to large problem instances, we make use of the idea of greedy stochastic search, and present a greedy stochastic algorithm, QPSD-GSA that provides moderately good solutions very rapidly even for large problems. The major contribution of the current paper is to apply QPSD-GSA to generate a subset of the starting solutions for a new genetic algorithm, QPSD-GEN, which is shown to provide near-optimal solutions very quickly. Owing to its polynomial running time, QPSD-GEN can be used for much larger instances than QPSD-MDFBB can handle. Experimental results have been provided to demonstrate the performances of these algorithms. � 2013 Elsevier Ltd. All rights reserved.
dc.publisherSCOPUS
dc.publisherComputers and Industrial Engineering
dc.relation.ispartofseries67(1)
dc.subjectGenetic algorithm
dc.subjectGraph search
dc.subjectQuadratic penalty
dc.subjectSequence-dependent setup
dc.subjectSingle machine scheduling
dc.titleApplication of graph search and genetic algorithms for the single machine scheduling problem with sequence-dependent setup times and quadratic penalty function of completion times
dc.typeArticle
Appears in Collections:Management Information Systems

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