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COMPETITIVE ANALYSIS OF INTERRELATED PRICE ONLINE INVENTORY PROBLEMS WITH DEMANDS

Part of: Computational number theory

Published online by Cambridge University Press:  15 May 2017

SHUGUANG HAN Open the ORCID record for SHUGUANG HAN [Opens in a new window] ,
JUELIANG HU  and
DIWEI ZHOU Open the ORCID record for DIWEI ZHOU [Opens in a new window]
SHUGUANG HAN*
Affiliation:
Department of Mathematics, Zhejiang Sci-Tech University, Hangzhou 310018, China email dawn1024@zstu.edu.cn email hujlhz@163.com
JUELIANG HU
Affiliation:
Department of Mathematics, Zhejiang Sci-Tech University, Hangzhou 310018, China email dawn1024@zstu.edu.cn email hujlhz@163.com
DIWEI ZHOU
Affiliation:
Department of Mathematical Sciences, Loughborough University, LoughboroughLE11 3TU, UK email d.zhou2@lboro.ac.uk
*
✉dawn1024@zstu.edu.cn
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Abstract

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This paper investigates interrelated price online inventory problems, in which decisions as to when and how much of a product to replenish must be made in an online fashion to meet some demand even without a concrete knowledge of future prices. The objective of the decision maker is to minimize the total cost while meeting the demands. Two different types of demand are considered carefully, that is, demands which are linearly and exponentially related to price. In this paper, the prices are online, with only the price range variation known in advance, and are interrelated with the preceding price. Two models of price correlation are investigated, namely, an exponential model and a logarithmic model. The corresponding algorithms of the problems are developed, and the competitive ratios of the algorithms are derived as the solutions by use of linear programming.

Keywords

interrelated pricesonline inventory problemcompetitive analysisdemand

MSC classification

Primary: 11Y16: Algorithms; complexity
Type
Research Article
Information
The ANZIAM Journal , Volume 58 , Issue 3-4 , April 2017 , pp. 368 - 378
Copyright
© 2017 Australian Mathematical Society 

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