Technical Note---Note on “Myopic Heuristics for the Random Yield Problem”
Karl Inderfurth () and
Sandra Transchel ()
Additional contact information
Karl Inderfurth: Faculty of Economics and Management, Otto-von-Guericke-University Magdeburg, 39106 Magdeburg, Germany
Sandra Transchel: Department of Logistics, University of Mannheim, 68131 Mannheim, Germany
Operations Research, 2007, vol. 55, issue 6, 1183-1186
Abstract:
Bollapragada and Morton (1999) present several well-performing heuristics for solving the periodic inventory problem with random yield and demand. Their approach is essentially based on a transformation of the single-period problem into a standard newsvendor problem with deterministic yield and random demand which, however, is supply dependent. In our note, we show that their evaluation of the respective optimality condition is not correct. This explains the steady deterioration of their myopic heuristics for parameter constellations that correspond to increasing service levels. Some computational investigations reveal that the performance of the heuristics can become quite poor if service levels are high and exceed those values for which results are reported in the original study. Nonetheless, up to now these heuristics are still the best ones available for solving the joint random yield problem.
Keywords: inventory/production; heuristics; stochastic (search for similar items in EconPapers)
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://dx.doi.org/10.1287/opre.1070.0420 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:55:y:2007:i:6:p:1183-1186
Access Statistics for this article
More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().