Optimal replenishment under price uncertainty

被引:8
|
作者
Mohr, Esther [1 ]
机构
[1] Univ Mannheim, Sch Business, D-68131 Mannheim, Germany
关键词
Inventory; Online algorithms; Minimax regret; Competitive ratio; Optimal search; TIME-SERIES SEARCH; ONLINE INVENTORY PROBLEM; COMPETITIVE ANALYSIS; OPTIMAL-ALGORITHMS; K-SEARCH; OIL; INVESTMENT;
D O I
10.1016/j.ejor.2016.08.011
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
We aim to find optimal replenishment decisions without having the entire price information available at the outset. Although it exists, the underlying price distribution is neither known nor given as part of the input. Under the competitive ratio optimality criterion, we design and analyze online algorithms for two related problems. Besides the reservation price based decision how much to buy we additionally consider the optimal scheduling of orders. We suggest an online algorithm that decides how much to buy at the optimal point in time and experimentally explore its decision making. Results show that the problem of finding a replenishment strategy with best possible worst-case performance guarantees can be considered as an extension of the online time series search problem. (C) 2016 Elsevier B.V. All rights reserved.
引用
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页码:136 / 143
页数:8
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