Newsvendor solutions with general random yield distributions

Scott E. Grasman; Zaki Sari; Tewfik Sari

RAIRO - Operations Research (2007)

  • Volume: 41, Issue: 4, page 455-464
  • ISSN: 0399-0559

Abstract

top
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.

How to cite

top

Grasman, Scott E., Sari, Zaki, and Sari, Tewfik. "Newsvendor solutions with general random yield distributions." RAIRO - Operations Research 41.4 (2007): 455-464. <http://eudml.org/doc/249939>.

@article{Grasman2007,
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. },
author = {Grasman, Scott E., Sari, Zaki, Sari, Tewfik},
journal = {RAIRO - Operations Research},
keywords = {Newsvendor model; operations management; planning and control; random yield; newsvendor model},
language = {eng},
month = {10},
number = {4},
pages = {455-464},
publisher = {EDP Sciences},
title = {Newsvendor solutions with general random yield distributions},
url = {http://eudml.org/doc/249939},
volume = {41},
year = {2007},
}

TY - JOUR
AU - Grasman, Scott E.
AU - Sari, Zaki
AU - Sari, Tewfik
TI - Newsvendor solutions with general random yield distributions
JO - RAIRO - Operations Research
DA - 2007/10//
PB - EDP Sciences
VL - 41
IS - 4
SP - 455
EP - 464
AB - 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.
LA - eng
KW - Newsvendor model; operations management; planning and control; random yield; newsvendor model
UR - http://eudml.org/doc/249939
ER -

References

top
  1. R.E. Bohn and C. Terwiesch, The Economics of Yield Driven Processes. J. Oper. Manage.19 (1999) 41–59.  
  2. S. Bollapragada, and T.E. Morton, Myopic Heuristics For the Random Yield Problem. Oper. Res.47 (1999) 713–722.  
  3. Y. Gerchak, R.G. Vickson and M. Parlar, Periodic Review Production Models with Variable Yield and Uncertain Demand. IIE Trans.20 (1988) 144–150.  
  4. S. Gilbert and H. Emmons, Managing a Deteriorating Process in a Batch-Production Environment. IIE Trans.27 (1993) 233–243.  
  5. S.E. Grasman, Capacitated Multiple Product Systems with Random Yield. Working Paper.  
  6. S.E. Grasman, T.L. Olsen and J.R. Birge, Setting Basestock Levels in Multiproduct Systems with Setups and Random Yield. IIE Trans. (to appear).  
  7. A. Grosfeld-Nir and Y. Gerchak, Multiple Lotsizing in Production to Order with Random Yields: A Review of Recent Advances. Ann. Oper. Res.26 (2004) 43–69.  
  8. M. Henig and Y. Gerchak, The Structure of Periodic Review Policies in the Presence of Random Yield. Oper. Res.38 (1990) 634–643.  
  9. D.P. Heyman and M.J. Sobel, Stochastic Models in Operations Research, Vol. II: Stochastic Optimization. McGraw-Hill (1984).  
  10. M. Khouja, The Single-Period (Newsvendor) Problem: Literature Review and Suggestions for Future Research. OMEGA Int. J. Manag. Sci. 27 (1999) 573–553.  
  11. W. Shih, Optimal Inventory Policies When Stockouts Result From Defective Products. Int. J. Prod. Res.18 (1980) 677–686.  
  12. C.A. Yano and H.L. Lee, Lot Sizing with Random Yields: A Review. Oper. Res.43 (1995) 311–334.  

NotesEmbed ?

top

You must be logged in to post comments.