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Non-permutation flowshop scheduling in a supply chain with sequence-dependent setup times

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dc.creator Mehravaran, Yasaman
dc.creator Logendran, Rasaratnam
dc.date.accessioned 2012-10-16T17:25:34Z
dc.date.available 2012-10-16T17:25:34Z
dc.date.issued 2012-02
dc.identifier.citation Mehravaran, Y., & Logendran, R. (2012). Non-permutation flowshop scheduling in a supply chain with sequence-dependent setup times. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 135(2), 953-963. doi: 10.1016/j.ijpe.2011.11.011 en_US
dc.identifier.uri http://hdl.handle.net/1957/34435
dc.description This is the author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/international-journal-of-production-economics/. en_US
dc.description.abstract In this paper, we consider a flowshop scheduling problem with sequence-dependent setup times and a bicriteria objective to minimize the work-in-process inventory for the producer and to maximize the customers' service level. The use of a bicriteria objective is motivated by the fact that successful companies in today's environment not only try to minimize their own cost but also try to fulfill their customers' need. Two main approaches, permutation and non-permutation schedules, are considered in finding the optimal schedule for a flowshop. In permutation schedules the sequence of jobs remains the same on all machines whereas in non-permutation schedule, jobs can have different sequence on different machines. A linear mathematical model for solving the non-permutation flowshop is developed to comply with all of the operational constraints commonly encountered in the industry, including dynamic machine availabilities, dynamic job releases, and the possibility of jobs skipping one or more machines, should their operational requirements deem that it was necessary. As the model is shown to be NP-hard, a metasearch heuristic, employing a newly developed concept known as the Tabu search with embedded progressive perturbation (TSEPP) is developed to solve, in particular, industry-size problems efficiently. The effectiveness and efficiency of the search algorithm are assessed by comparing the search algorithmic solutions with that of the optimal solutions obtained from CPLEX in solvable small problem instances. en_US
dc.description.sponsorship The research reported in this paper is funded in part by the National Science Foundation (USA) Grant no. CMMI-1029471. en_US
dc.language.iso en_US en_US
dc.publisher Elsevier en_US
dc.relation.ispartofseries International Journal of Production Economics en_US
dc.relation.ispartofseries Vol. 135 no. 2 en_US
dc.subject Flowshop en_US
dc.subject Bicriteria en_US
dc.subject Sequence-dependent setup time en_US
dc.subject Non-permutation scheduling en_US
dc.subject Mixed-integer linear programming en_US
dc.subject Tabu search with embedded progressive perturbations en_US
dc.title Non-permutation flowshop scheduling in a supply chain with sequence-dependent setup times en_US
dc.type Article en_US
dc.description.peerreview yes en_US
dc.identifier.doi 10.1016/j.ijpe.2011.11.011

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