A higher-order Markov model for the Newsboy's problem
W K Ching (),
E S Fung and
M K Ng
Additional contact information
W K Ching: The University of Hong Kong
E S Fung: The University of Hong Kong
M K Ng: The University of Hong Kong
Journal of the Operational Research Society, 2003, vol. 54, issue 3, 291-298
Abstract:
Abstract Markov models are commonly used in modelling many practical systems such as telecommunication systems, manufacturing systems and inventory systems. However, higher-order Markov models are not commonly used in practice because of their huge number of states and parameters that lead to computational difficulties. In this paper, we propose a higher-order Markov model whose number of states and parameters are linear with respect to the order of the model. We also develop efficient estimation methods for the model parameters. We then apply the model and method to solve the generalised Newsboy's problem. Numerical examples with applications to production planning are given to illustrate the power of our proposed model.
Keywords: higher-order Markov model; Newsboy's model; shortage cost; overage cost (search for similar items in EconPapers)
Date: 2003
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://link.springer.com/10.1057/palgrave.jors.2601491 Abstract (text/html)
Access to full text is restricted to subscribers.
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:pal:jorsoc:v:54:y:2003:i:3:d:10.1057_palgrave.jors.2601491
Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/41274
DOI: 10.1057/palgrave.jors.2601491
Access Statistics for this article
Journal of the Operational Research Society is currently edited by Tom Archibald and Jonathan Crook
More articles in Journal of the Operational Research Society from Palgrave Macmillan, The OR Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().