Optimal two-stage ordering policy with Bayesian information updating

Tsan Ming Choi, D. Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

93 Citations (Scopus)

Abstract

We investigate in this paper an optimal two-stage ordering policy for seasonal products. Before the selling season, a retailer can place orders for a seasonal product from her supplier at two distinct stages satisfying the lead-time requirement. Market information is collected at the first stage and is used to update the demand forecast at the second stage by using Bayesian approach. The ordering cost at the first stage is known but the ordering cost at the second stage is uncertain. A two-stage dynamic optimization problem is formulated and an optimal policy is derived using dynamic programming. The optimal ordering policy exhibits nice structural properties and can easily be implemented by a computer program. The detailed implementation scheme is proposed. The service level and profit uncertainty level under the optimal policy are discussed. Extensive numerical analyses are carried out to study the performance of the optimal policy.
Original languageEnglish
Pages (from-to)846-859
Number of pages14
JournalJournal of the Operational Research Society
Volume54
Issue number8
DOIs
Publication statusPublished - 1 Aug 2003
Externally publishedYes

Keywords

  • Bayesian information updating
  • Dynamic programming
  • Inventory control

ASJC Scopus subject areas

  • Management Information Systems
  • Strategy and Management
  • Management Science and Operations Research
  • Marketing

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