BATCH ORDERING INVENTORY MANAGEMENT UNDER THE MIXED DEMAND INFORMATION: A CASE STUDY

Year 2020, , 666 - 677, 03.09.2020

Muzaffer Alım , Patrick Beullens

https://doi.org/10.36306/konjes.599332

Cited By: 1

Abstract

This study is concerned with analysing the past demand data and development of an
inventory model with demand arising from deterministic which is known in advance and random sources
simultaneously. Two different shortages are created for each demand type and in order to prevent model
to backlog the deterministic demand, very high shortage cost is given for deterministic demand. The
numerical value of the parameters are obtained from a real case which the inventory system of an
information and technological organization of a university. The main difference of this study from the
previous studies is that the order amount must be in palette quantity for a deterministic and stochastic
demand inventory problem. Under this constraint, an inventory model is developed and tested with
several datasets. Assuming lead time as constant, the value of deterministic demand present in the system
and impact of palette constraint are investigated. These investigations are compared with the status quo
in the case study. It has seen that the palette quantity behaves as safety stock for high level random
demand. Recommendations based on the impacts of advance demand information, lead time and pallet
quantity are presented in terms of changing in ordering costs, holding costs and service level.

Keywords

Inventory model, batch ordering, deterministic and stochastic demand, mix integer programming

Karışık Talep Bilgisi Kapsamında Toplu Sipariş Envanter Yönetimi: Bir Durum Çalışması

Abstract

Bu çalışma, geçmiş dönem talep bilgisinin ve önceden bilinen deterministik ve rassal talep bilgisinin
birlikte bulunduğu stok sistemlerinin analizini konu almaktadır. Herbir talep bilgisi için iki farklı talebi
karşılayamama maliyeti belirlenmiş olup deterministik talebe verilen yüksek talep karşılayamama
maliyeti bu tip talebin zamanında karşılanmamasını oldukça güç hale getirmektedir. Kullanılan veriler
bir üniversitenin bilgi teknolojilerinden sorumlu olan birimden alınmıştır. Bu çalışmanın literatürdeki
diğer çalışmalardan farkı aynı anda hem deterministik hem de rassal talep altında sipariş miktarının palet
cinsinden olmasıdır. Bu kısıt altında, bir stok modeli geliştirilmiş ve farklı veriler altında sayısal olarak
test edilmiştir. Sabit tedarik süresi varsayımı altında, deterministik talebin değeri ve paletle sipariş
kısıtının etkileri ölçülmüştür. Bu ölçümler, mevcut durumla kıyaslanmıştır. Paletin içerik miktarının
yüksek seviyedeki rassal talep için güvenli stok olarak davrandığı gözlemlenmiştir. Değişen sipariş
maliyeti, stok tutma maliyeti ve hizmet seviyeleri altında ön talep bilgisi, tedarik süresi ve palet miktarının
etkileri üzerine önerilerde bulunulmuştur.

Keywords

Envanter modelleme, yığın sipariş kısıtı, deterministik ve rassal talep, matematiksel modelleme

References

• Aloulou, M., Dolgui, A. and Kovalyov, M. (2013). A bibliography of non-deterministic lot-sizing models. International Journal of Production Research, 52(8), pp.2293-2310.
• Bon, A. and Leng, C. (2009). The Fundamental on Demand Forecasting in Inventory Management. Australian Journal of Basic and Applied Sciences, 3(4), pp.3937--3943.
• Bushuev, M., Guiffrida, A., Jaber, M. and Khan, M. (2015). A review of inventory lot sizing review papers. Management Research Review, 38(3), pp.283-298.
• Chao, X. and Zhou, S. (2009). Optimal Policy for a Multiechelon Inventory System with Batch Ordering and Fixed Replenishment Intervals. Operations Research, 57(2), pp.377-390.
• Chen, F. (2000). Optimal Policies for Multi-Echelon Inventory Problems with Batch Ordering. Operations Research, 48(3), pp.376-389.
• Chen, F. and Zheng, Y. (1994). Evaluating Echelon Stock (R, nQ) Policies in Serial Production/Inventory Systems with Stochastic Demand. Management Science, 40(10), pp.1262-1275.
• Gallego, G. and Ozer, Özalp. (2001). Integrating replenishment decisions with advance demand information. Management Science, 47(10), pp.1344--1360.
• Kesen, S. E., Kanchanapiboon, A. and Das, S. (2010). Evaluating supply chain flexibility with order quantity constraints and lost sales. International Journal of Production Economics, 126(2), pp.181-188.
• Özer, Ö. and Wei, W. (2004). Inventory Control with Limited Capacity and Advance Demand Information. Operations Research, 52(6), pp.988-1000.
• Shang, K. and Zhou, S. (2010). Optimal and Heuristic Echelon (r, nQ, T) Policies in Serial Inventory Systems with Fixed Costs. Operations Research, 58(2), pp.414-427.
• Sobel, M. and Zhang, R. (2001). Inventory policies for systems with stochastic and deterministic demand. Operations research, 49(1), pp.157--162.
• Taha, H. (2007). Operation Research: An Introduction. 8th ed. New Jersey: Pearson, pp.427-449.
• Veinott, A. (1965). The Optimal Inventory Policy for Batch Ordering. Operations Research, 13(3), pp.424- 432.
• Wang, T. and Toktay, B. (2008). Inventory management with advance demand information and flexible delivery. Management Science, 54(4), pp.716--732.
• Waters, C. (1992). Inventory control and management. 1st ed. Chichester [England]: Wiley.
• Van Woensel, T., Erkip, N., Curseu, A. and Fransoo, J.C., 2013. Lost sales inventory models with batch ordering and handling costs. In Beta Working Paper series. Eindhoven (Vol. 421).