Abstract

This article studies a single-item periodic-review inventory problem with stochastic demand, uncertain price, and price search cost. At the beginning of a period, an inventory manager has to decide, considering the current inventory level, whether a price should be searched for at a non-zero cost. Once the price is known, she will have to decide the order size. For tractability the number of realizable prices is limited to two and (r, S1, S2)-type policies are considered, where r is the threshold for the price search decision and Si is the order-up-to level for price pi for i = 1, 2. Although the problem is significantly simplified, it still allows for price speculations by the inventory manager; i.e., she requests a quote but may not buy. The properties of long-run average costs are studies and optimization algorithms are presented. Numerical studies show the effectiveness of the proposed policy compared with classic (s, S)-type policy and its natural three-parameter extension.

Highlights

  • Inventory management has become an important aspect of economic activities due to the tremendous investment in inventory systems, as Nahmias (2005) points out

  • An (r, S1, S2) policy with r < S2, S1 ≤ S2 is proposed for the problem with two prices

  • The properties of the total cost functions are first studied, and the optimization algorithms are devised based on the properties of the cost functions

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Summary

A Stochastic Inventory Model with Price Quotation

This thesis studies a single item periodic review inventory management problem with stochastic demand, random price and quotation cost. An (r, S1, S2) policy with r < S2, S1 ≤ S2 is proposed for the problem with two prices It prescribes that when the inventory is less than or equal to r, the price quotation is requested; if the higher price is quoted, order up to S1, otherwise to S2. It reveals that in some cases it is optimal to search price speculatively, that is with S1 < r, to request a quote but only place an order when the lower price is realized, when the inventory level is between S1 and r

Introduction
CHAPTER 1. INTRODUCTION
Problem Description
Literature Review
Research Objective and Contribution
Thesis Outline
Preliminary
Properties of the Total Cost Functions
Optimization Algorithm
Chapter 4 Numerical Studies
Some Examples
CHAPTER 4. NUMERICAL STUDIES
Tests of the Optimization Algorithms
Conclusion
CONCLUSION AND FUTURE
Future Research and Extensions
Proof of Lemma 1
Proof of Lemma 3
Findings
Proof of Lemma 14
Full Text
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