Journals / Anadolu Üniversitesi Bilim ve Teknoloji Dergisi :A-Uygulamalı Bilimler ve Mühendislik / 2016 / Cilt: 17 - Sayı: 2

A COORDINATED INVENTORY AND PRICING MODEL FOR PERISHABLE PRODUCTS

KISA ÖMÜRLÜ ÜRÜNLER İÇİN KOORDİNELİ BİR STOK VE FİYAT YÖNETİMİ MODELİ

Pages
423–437
Publication Date
2022-10-11
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Through numerical studies, we analyse the effects of the parameters on the optimal results and try to extract managerial implications.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, coordinated inventory control and pricing decisions for perishable products, such as milk, yogurt, eggs, bread, fresh fruits, etc., considering an age-dependent demand function, is considered.
📊
Key Findings & Data:Different from durable products, tEndüstri Mühendisliği Bölümü, he demand for perishable products decrease as they age, and they can become totally obsolete in a short time period.
💡
Conclusion & Impact:Through numerical studies, we analyse the effects of the parameters on the optimal results and try to extract managerial implications.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this study, coordinated inventory control and pricing decisions for perishable products, such as milk, yogurt, eggs, bread, fresh fruits, etc., considering an age-dependent demand function, is considered. Different from durable products, tEndüstri Mühendisliği Bölümü, he demand for perishable products decrease as they age, and they can become totally obsolete in a short time period. Thus, not only the quantity of these products at hand, but also their age and freshness affect their inventory and pricing decisions, leading to a more complicated problem. As these products age, they will be demanded less and the customers might decide to go to other sellers. In this study, we build a model for the coordinated inventory and pricing management of perishable products, and we analyse the optimal solution of this model. We also propose an approximation algorithm for the cases when the optimal solution is difficult to find. Through numerical studies, we analyse the effects of the parameters on the optimal results and try to extract managerial implications.

Özet

Bu çalışmada süt, yoğurt, yumurta, ekmek, taze meyve-sebze gibi kısa ömürlü dayanıksız ürünler için, zamana bağlı bir talep fonksiyonu gözetilerek, koordineli stok yönetimi ve fiyatlandırma kararları konu alınmaktadır. Dayanıklı ürünlerden farklı olarak, bu ürünler eskidikçe müşteriler tarafından daha az tercih edilmeye başlamakta ve kısa bir zaman içerisinde tamamen kullanılamaz hale gelebilmektedir. Dolayısıyla, herhangi bir anda elde bulunan ürünlerin sadece miktarları değil, durumları veya yaşları da stok ve fiyatlandırma kararlarına etki etmekte ve problemi zorlaştırmaktadır. Yeni ve taze ürünlere olan talep fazla iken, ürünler eskidikçe müşteriler tarafından daha az tercih edilmekte ve bazı müşteriler başka ürünlere yönelebilmektedir. Bu çalışmada kısa ömürlü ürünlerin stok ve fiyat yönetimi için bir model oluşturulmuş ve bu modelin analizi ile en iyi çözümü araştırılmıştır. Oluşturulan modelin en iyi çözümünün bulunmasının mümkün olmadığı durumlar için bir yaklaşım algoritması da geliştirilmiştir. Ayrıca, sayısal çalışmalar ile farklı durumlarda uygulanması gereken yöntemler ortaya çıkarılmış ve öneriler geliştirilmiştir.

🔖

Cite This Article

KAYA, O. (2022). A COORDINATED INVENTORY AND PRICING MODEL FOR PERISHABLE PRODUCTS. Anadolu Üniversitesi Bilim ve Teknoloji Dergisi :A-Uygulamalı Bilimler ve Mühendislik, Cilt: 17 - Sayı: 2, 423–437. https://ajindex.com/articles/438356

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (10)

  1. Minner, S, Transchel, S. Periodic review inventory-control for perishable products under service- level constraints. OR Spectrum, 2010; 32(4): 979-996. Broekmeulen RACM, van Donselaar KH. A heuristic to manage perishable inventory with batch ordering, positive lead-times, and time-varying demand. Computers and Operations Research, 2009; 36: 3013-3018.
  2. Nahmias, S. Perishable inventory theory: a review. Operations Research, 1982; 30: 680-708.
  3. Rafaat, F. Survey of literature on continuously deteriorating inventory models. Journal of Operations Research Society, 1991; 42(1): 27-37.
  4. Goyal SK, Giri BC. Recent trends in modeling of deteriorating inventory. European Journal of Operational Research, 2001; 134(1): 1-16.
  5. Karaesmen I, Scheller-Wolf A, Deniz B. Managing perishable and aging inventories: review and future research directions. In: Kempf K, Keskinocak P, Uzsoy R, editors. Planning Production and Inventories in the Extended Enterprise, Volume 151 of the series International Series in Operations Research & Management Science, Springer, 2008: 393-436. van Zyl, G. Inventory control for perishable commodities. Ph.D. thesis, University of North Carolina, Chapel Hill, NC, 1964.
  6. Nahmias, S. Optimal ordering policies for perishable inventory - II. Operations Research, 1975; 23(4): 735-749. Fries B. Optimal ordering policy for a perishable commodity with fixed lifetime. Operations Research, 1975; 23(1): 46-61.
  7. Ferguson N, Ketzenberg ME. Informations Sharing to Improve Retail Product Freshness of Perishable Products. Production and Operations Management, 2006; 15(1): 57-73. van Donselaar KH, de Kok AG., Rutten WGMM. Two replenishment strategies for the lost sales inventory model: a comparison. International Journal of Production Economics, 1996; 47(1): 285-295. [12] Parlar M, Perry D, Stadje W. FIFO Versus LIFO Issuing Policies for Stochastic Perishable Inventory Systems. Methodology & Computing in Applied Probability, 2010; 12: 1-13.
  8. Berk E, Gürler Ü. Analysis of the (Q, r) inventory model for perishables with positive lead times and non-negligible ordering costs. Operations Research, 2008; 56: 1238-1246. Schultz CR. Replenishment delays for expensive slow moving items. Management Science, 1989; 35: 1454-1462.
  9. Tekin, E, Gürler, Ü, Berk, E. Age-based vs. stock level control policies for a perishable inventory system. European Journal of Operational Research, 2001; 134: 309-329.
  10. Gallego, G, van Ryzin, G. Optimal dynamic pricing of inventories with stochastic demand o