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Flow Formulation of Demand Propagation in Guaranteed Service Models

DOI zum Zitieren der Version auf EPub Bayreuth: https://doi.org/10.15495/EPub_UBT_00006986
URN to cite this document: urn:nbn:de:bvb:703-epub-6986-3

Title data

Kamp, Dominik ; Rambau, Jörg:
Flow Formulation of Demand Propagation in Guaranteed Service Models.
In: IFAC-PapersOnLine. Vol. 55 (2022) Issue 20 . - pp. 505-510.
ISSN 2405-8963
DOI der Verlagsversion: https://doi.org/10.1016/j.ifacol.2022.09.145

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Name:	Kamp+Rambau_F-SGSM-DP_MATHMOD_2022.pdf
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Project information

Project title:	Project's official title Project's id The Stochastic Guaranteed Service Model with Demand Propagation (SGSM-DP) RA 1033/3-1
Project financing:	Deutsche Forschungsgemeinschaft

Abstract

In this paper we present two alternative models for the Stochastic Guaranteed Service Model with Demand Propagation (SGSM-DP) in multi-echelon inventory theory. While the original SGSM-DP could so far not be solved for standard networks with more than 15 nodes in 1000 seconds, the new equivalent model F-SGSM-DP based on dynamic flows with arcs going backwards in time can be solved even for heavy instances with up to around 50 nodes.

Further data

Item Type:	Article in a journal
Additional notes (visible to public):	Der hier vorliegende Volltext ist die accepted version
Keywords:	operation research; logistics; planning; comparison of methods for modeling; optimization; multi-echelon inventory management; stochastic programming; network flow; guaranteed service model; mixed-integer linear programming; demand propagation
Subject classification:	MSC2010 90B05
DDC Subjects:	500 Science > 510 Mathematics
Institutions of the University:	Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematical Economics > Chair Mathematical Economics - Univ.-Prof. Dr. Jörg Rambau Research Institutions > Central research institutes > Bayreuth Research Center for Modeling and Simulation - MODUS Graduate Schools > University of Bayreuth Graduate School Graduate Schools > Bayreuth Graduate School of Mathematical and Natural Sciences (BayNAT) > Computational Mathematics in Science and Engineering Faculties Faculties > Faculty of Mathematics, Physics und Computer Science Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematical Economics Research Institutions Research Institutions > Central research institutes Graduate Schools Graduate Schools > Bayreuth Graduate School of Mathematical and Natural Sciences (BayNAT)
Language:	English
Originates at UBT:	Yes
URN:	urn:nbn:de:bvb:703-epub-6986-3
Date Deposited:	11 May 2023 09:32
Last Modified:	11 May 2023 09:33
URI:	https://epub.uni-bayreuth.de/id/eprint/6986

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