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Newsvendor solutions with general random yield distributions

Published online by Cambridge University Press:  11 October 2007

Scott E. Grasman
Affiliation:
219 EMSE, University of Missouri - Rolla, Rolla, Missouri 65409-0370, USA; grasmans@umr.edu
Zaki Sari
Affiliation:
Laboratoire d'Automatique de Tlemcen, Faculté des Sciences de l'Ingénieur, Université Abou Bekr Belkaïd de Tlemcen, Algeria; z_sari@univ-tlemcen.edu
Tewfik Sari
Affiliation:
Mathematics, University of Mulhouse, France; t.sari@uha.fr
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Abstract

Most systems are characterized by uncertainties that cause throughput to be highly variable, for example, many modern production processes and services are substantially affected by random yields. When yield is random, not only is the usable quantity uncertain, but the random yield reduces usable capacity and throughput in the system. For these reasons, strategies are needed that incorporate random yield. This paper presents the analysis of the newsvendor model with a general random yield distribution, including the derivation of the optimal order quantity. Results are shown to converge to the basic newsvendor model for the case of perfect yield, and are further demonstrated using the case of general multiplicative random yield. Results have significant impact on both manufacturing and service sectors since the newsvendor model applies to many real-world situations.

Type
Research Article
Copyright
© EDP Sciences, ROADEF, SMAI, 2007

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