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Reverse logistics concerns the integration of used and obsolete products back into the supply chain as valuable resources. Economic, marketing, and legislative drivers increasingly are leading companies to take back and recover their products after use. The arising product flows pose novel challenges for supply chain management. This book addresses decision making in reverse logistics. It covers a wide range of aspects, related to distribution, production and inventory management, and supply chain management. For each topic, it highlights key managerial issues in real-life examples and explains which quantitative models are available for addressing them. By treating a broad range of issues in a unified way, the book offers the reader a comprehensive view on the field of reverse logistics.
Reverse logistics concerns the integration of used and obsolete products back into the supply chain as valuable resources. Economic, marketing, and legislative drivers increasingly are leading companies to take back and recover their products after use. The arising product flows pose novel challenges for supply chain management. This book addresses decision making in reverse logistics. It covers a wide range of aspects, related to distribution, production and inventory management, and supply chain management. For each topic, it highlights key managerial issues in real-life examples and explains which quantitative models are available for addressing them. By treating a broad range of issues in a unified way, the book offers the reader a comprehensive view on the field of reverse logistics.
Ian M. Langella examines the planning of disassembly for
remanufacturing of used products, yielding components which are
reassembled into as good as new items.
This volume contains a selection of manuscripts referring to lectures presented at the Symposium on Operations Research 1999 (SOR'99) held at the Otto-von-Guericke University Magdeburg, Sep- tember 1 -3, 1999. This international conference took place under the auspices of the German OR society (GOR), and it was the first one organized in Germany since the foundation of GOR by merger of the two predecessor societies (DGOR and GMOOR) in 1998. The Symposium had 420 participants from 22 countries around the world. It attracted academicians and practitioners working in various fields of Operations Research and provided them with the most recent developments and advances in the full spectrum of Operations Research and related areas in economics, mathematics, and computer science. The selection of contributions to SOR'99 accepted by the program committee and the invited pa- pers formed a program which consisted of 265 lectures in 19 sections, including 2 plenary and 19 semi plenary presentations. 119 manuscripts were submitted for publication in the proceedings vo- lume. Due to the page limit for this volume and in order to insure a high quality level of the OR Proceedings a further review procedure had to take place which was strongly supported by the sec- tion chairpersons. It resulted in a selection of 87 manuscripts which are now presented in this volume.
Die vorliegende Arbeit "Zur Gute linearer Entscheidungsregeln in Produktions- Lagerhaltungs-Modellen" wurde 1975 vom Fachbereich Wirtschaftswissenschaften der Freien Universitat Berlin als Dissertation angenommen. Herrn Prof. Dr. Christoph Schneewei mochte ich fur die Anregung zur Bearbei- tung dieses Themas und fur die stetige Unterstiitzung herzlich danken. Der Deutschen Forschungsgemeinschaft bin ich dankbar fUr die finanzielle Forderung dieser Arbeit im Rahmen des Forschungsprojekts "Theil'sche Theorie" (Schn 159/1 u. 2). Berlin, November 1976 Karl Inderfurth 3 Inhalt 1. Problemstellung ...................................... . 7 2. Darstellung einer Klasse von Produktions-Lagerhaltungs-Modellen ...... . 10 3. Die Anwendung der stochastischen dynamischen Optimierung ........ . 16 3.1. Die optimale Politik im Grundmodell ..................... . 16 3.1.1. Die Struktur der optimalen Politik ................... . 16 3.1.2. Die Ermittlung der Politik-Parameter. ................. . 18 3.1.2.1. Aufstellung und Auswertung der Funktionalgleichungen ..................... . 18 3.1. 2.2. Untersuchung der Politikparameter durch Wertiteration 22 3.1.2.3. Iterationsverfahren zur Berechnung der Politik-Parameter ............... . 28 3.1.3.Die Ermittlung der minimalen Kosten ....... . 31 3.1.4. Sensitivitatsanalyse ............................. . 35 3.2. Die optimale Politik im Modell mit Fixkosten ................ . 38 3.2.1. Zur Struktur der optimalen Politik ........... . 38 3.2.2.Die Ermittlung der optimalen Politik und Durchschnittskosten . . . . . . . . . . . . . . . . . . . . .. . . 41 . . . . . 3.2.2.1. Darstellung des Problems als Markovschen Entscheidungsproze . . . . . . . . . . . . . . . .. . . . 41 . . . 3.2.2.2. Ein LP-Ansatz zur Losung des Markovschen Entscheidungsproblems . . . . . . . . . . . . . . .. . . . 45 . . 3.2.2.3. Die Ergebnisse der numerischen Berechnungen . . 52 3.2.3. Ein Iterationsverfahren zur Bestimmung der Parameter der optimalen Politik . . . . . . . . . . . . . . . . . . . . . . 53 . . . 3.2.4. Sensitivitatsanalyse . . . . . . . . . . . . . . . . . . . . .. . . . 58 . . . . .
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