Optimal lot-size and Price of Perishable Goods: A novel Game-Theoretic Model using Double Interval Grey Numbers. (November 2020)

• Record Type: Journal Article
• Authors: Hendalianpour, Ayad
• Is Part Of: Computers & industrial engineering. Volume 149(2020)
• Publication Date: 2020-11
• Subjects: Game-theoretic modeling -- Perishable goods -- Pricing -- Order quantity -- DIGN -- Product freshness; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2020.106780
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A new model is proposed for joint lot-sizing and pricing of perishable products. Demand depends on selling and reference prices, product freshness and safety stock. Double Interval Gray Numbers (DIGN) are employed to formulate the problem. Optimal policy is assessed based on loss-neutral and loss-averse demand functions. Sensitivity analysis is conducted to understand the impact of different parameters. Abstract: Industrial supply chain management is facing major challenges associated with supplying perishable products, particularly healthy and high-quality foods with a limited shelf-life that require specific inventory holding conditions. Consumers usually prefer product freshness over its price when making buying decision since they will be able to keep it for a longer term. Demand is considered to be a function of the selling price and reference price as well as the freshness of products associated with their expiry dates and safety stock levels. The model is developed taking advantage of Double Interval Grey Numbers (DIGN) to more accurately formulate consumer behavior and enhance quality of the analytical results in practical decision-making. Moreover, the optimal retailer decision provided by the model is discussed when losing the market share and when there is no consistency between product freshness and price. The present study is conducted to develop and propose a game-theoretic model for the joint decisions made on pricing and lot-sizing by retailers of perishable goods. Numerical experiments confirm the consistency of the optimal pricing and inventory strategies and show that the system was uniquely balanced for different demand scenarios. Sensitivity analysis is also presented to identify the structural characteristics of the problem and understand the impact of different parameters on optimal decision-making.