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|a A fix-and-optimize approach for the multi-level capacitated lot sizing problem
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|a This paper presents an optimization-based solution approach for the dynamic multi-level capacitated lot sizing problem (MLCLSP) with positive lead times. The key idea is to solve a series of mixed-integer programs in an iterative fix-and-optimize algorithm. Each of these programs is optimized over all real-valued variables, but only a small subset of binary setup variables. The remaining binary setup variables are tentatively fixed to values determined in previous iterations. The resulting algorithm is transparent, flexible, accurate and relatively fast. Its solution quality outperforms those of the approaches by Tempelmeier/Derstroff and by Stadtler.
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This paper presents an optimization-based solution approach for the dynamic multi-level capacitated lot sizing problem (MLCLSP) with positive lead times. The key idea is to solve a series of mixed-integer programs in an iterative fix-and-optimize algorithm. Each of these programs is optimized over all real-valued variables, but only a small subset of binary setup variables. The remaining binary setup variables are tentatively fixed to values determined in previous iterations. The resulting algorithm is transparent, flexible, accurate and relatively fast. Its solution quality outperforms those of the approaches by Tempelmeier/Derstroff and by Stadtler. |
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A fix-and-optimize approach for the multi-level capacitated lot sizing problem Stefan Helber; Florian Sahling, Hannover Fachbereich Wirtschaftswiss., Univ. 07 Mar. 2008, Online-Ressource, 22 S., Text, Text txt rdacontent, Computermedien c rdamedia, Online-Ressource cr rdacarrier, Discussion papers / School of Economics and Management of the Hanover Leibniz University 393, This paper presents an optimization-based solution approach for the dynamic multi-level capacitated lot sizing problem (MLCLSP) with positive lead times. The key idea is to solve a series of mixed-integer programs in an iterative fix-and-optimize algorithm. Each of these programs is optimized over all real-valued variables, but only a small subset of binary setup variables. The remaining binary setup variables are tentatively fixed to values determined in previous iterations. The resulting algorithm is transparent, flexible, accurate and relatively fast. Its solution quality outperforms those of the approaches by Tempelmeier/Derstroff and by Stadtler., Systemvoraussetzungen: Acrobat Reader., 1.1\x Produktionsplanung (DE-627)091384516 (DE-2867)12758-2 stw, 1.2\x Losgröße (DE-627)091375703 (DE-2867)12755-1 stw, 1.3\x Ganzzahlige Optimierung (DE-627)091361761 (DE-2867)15535-0 stw, 1.4\x Mehrstufige Produktion (DE-627)091377196 (DE-2867)10324-3 stw, 1.5\x Theorie (DE-627)091394902 (DE-2867)19073-6 stw, Arbeitspapier DE-206, Graue Literatur DE-206, Buch DE-206, Online-Publikation DE-206, Helber, Stefan 1963- (DE-588)121396584 (DE-627)081280858 (DE-576)292688954 oth, Sahling, Florian oth, Universität Hannover Wirtschaftswissenschaftliche Fakultät Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät 393 39300 (DE-627)36987773X (DE-576)281231680 (DE-600)2120102-X, http://diskussionspapiere.wiwi.uni-hannover.de/pdf_bib/dp-393.pdf Verlag kostenfrei Volltext, http://hdl.handle.net/10419/27203 Download aus dem Internet, Stand 01.04.2008 Volltext, http://diskussionspapiere.wiwi.uni-hannover.de/pdf_bib/dp-393.pdf LFER, LFER 2019-05-07T00:00:00Z |
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A fix-and-optimize approach for the multi-level capacitated lot sizing problem, Universität Hannover, Wirtschaftswissenschaftliche Fakultät, Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät, 393, This paper presents an optimization-based solution approach for the dynamic multi-level capacitated lot sizing problem (MLCLSP) with positive lead times. The key idea is to solve a series of mixed-integer programs in an iterative fix-and-optimize algorithm. Each of these programs is optimized over all real-valued variables, but only a small subset of binary setup variables. The remaining binary setup variables are tentatively fixed to values determined in previous iterations. The resulting algorithm is transparent, flexible, accurate and relatively fast. Its solution quality outperforms those of the approaches by Tempelmeier/Derstroff and by Stadtler., Produktionsplanung, Losgröße, Ganzzahlige Optimierung, Mehrstufige Produktion, Theorie, Arbeitspapier, Graue Literatur, Buch, Online-Publikation |
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A fix-and-optimize approach for the multi-level capacitated lot sizing problem |
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A fix-and-optimize approach for the multi-level capacitated lot sizing problem |
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A fix-and-optimize approach for the multi-level capacitated lot sizing problem Stefan Helber; Florian Sahling |
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A fix-and-optimize approach for the multi-level capacitated lot sizing problem Stefan Helber; Florian Sahling |
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A fix-and-optimize approach for the multi-level capacitated lot sizing problem Stefan Helber; Florian Sahling |
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393. A fix-and-optimize approach for the multi-level capacitated lot sizing problem (07 Mar. 2008) |
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A fix-and-optimize approach for the multi-level capacitated lot sizing problem |
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fix and optimize approach for the multi level capacitated lot sizing problem |
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