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Inventory Optimization for Multiple Perishable Products with Dynamic Pricing, Dependent Stochastic Demand, and Dynamic Reorder Policy

  • Hudaifah A. Syawal
  • , Hesham K. Alfares

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Inventory control is relatively difficult when the product is perishable, the demand is stochastic, the product life cycle is short, and the pricing policy is dynamic. Several prior studies utilized simulation approaches to deal with the high complexity, stochastic, and multi-factor nature of this problem. However, most previous studies considered only a single perishable product. In real life, there are many cases in which the stochastic demand for a perishable product is dependent on the stochastic demand for another perishable product. Therefore, this paper considers a multi-product inventory problem with stochastic and dependent demand under a dynamic pricing policy. Specifically, we consider a retail shop that sells two perishable products, where the demand for one product is stochastic and dependent on the stochastic demand for another product. Using Arena and its OptQuest tool, a simulation model is constructed and used to find the optimal values of the reorder-up-to-levels for both products in order to maximize the expected total profit. A case study is used to demonstrate the essential features of the model.

Original languageEnglish
Title of host publication2020 Industrial and Systems Engineering Conference, ISEC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728166407
DOIs
StatePublished - 11 Jul 2020

Publication series

Name2020 Industrial and Systems Engineering Conference, ISEC 2020

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

  • Dependent demand
  • Dynamic pricing
  • Perishable inventory
  • Simulation
  • Stochastic demand

ASJC Scopus subject areas

  • Organizational Behavior and Human Resource Management
  • Tourism, Leisure and Hospitality Management
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Control and Optimization

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