Risk management of two-period inventory models for perishable or deteriorating products based on conditional value-at-risk

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper considers inventory problems for perishable or deteriorating products to maximize the total profit considering high- and low-priority customers based on the conditional Value-at-Risk (cVaR). The cVaR is a useful risk measure in economics and finance, which satisfies all requirements of ideal risk measures such as coherence and stochastic dominance. In order to apply random sampling derived from known distributions or historical data to our proposed model and to develop an analytical and efficient solution algorithm, the scenario-based solution algorithm is developed by performing equivalent transformations into a linear programming problem. Furthermore, numerical examples are provided to compare our proposed model with the previous standard model based on the expected value for the total profit. Furthermore, the results also show differences from the previous cVaR-based model with only one demand under some random distributions.

Original languageEnglish
Pages (from-to)231-243
Number of pages13
JournalJournal of Japan Industrial Management Association
Volume64
Issue number2
Publication statusPublished - 2013
Externally publishedYes

Fingerprint

Conditional Value at Risk
Inventory Model
Risk Management
Risk management
Risk Measures
Profit
Stochastic Dominance
Random Sampling
Historical Data
Profitability
Efficient Solution
Expected Value
Finance
Standard Model
Linear programming
Analytical Solution
Customers
Maximise
Model
Economics

Keywords

  • Conditional value-at-risk
  • Inventory model
  • Perishable or deteriorating items
  • Scenario-based approach

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Applied Mathematics
  • Management Science and Operations Research
  • Strategy and Management

Cite this

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abstract = "This paper considers inventory problems for perishable or deteriorating products to maximize the total profit considering high- and low-priority customers based on the conditional Value-at-Risk (cVaR). The cVaR is a useful risk measure in economics and finance, which satisfies all requirements of ideal risk measures such as coherence and stochastic dominance. In order to apply random sampling derived from known distributions or historical data to our proposed model and to develop an analytical and efficient solution algorithm, the scenario-based solution algorithm is developed by performing equivalent transformations into a linear programming problem. Furthermore, numerical examples are provided to compare our proposed model with the previous standard model based on the expected value for the total profit. Furthermore, the results also show differences from the previous cVaR-based model with only one demand under some random distributions.",
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