BATCH ORDERING INVENTORY MANAGEMENT UNDER THE MIXED DEMAND INFORMATION: A CASE STUDY
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
References
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Details
Primary Language
English
Subjects
Engineering
Journal Section
Research Article
Authors
Muzaffer Alım
*
0000-0002-4420-7391
Türkiye
Patrick Beullens
This is me
0000-0001-6156-3550
United Kingdom
Publication Date
September 3, 2020
Submission Date
July 31, 2019
Acceptance Date
April 25, 2020
Published in Issue
Year 2020 Volume: 8 Number: 3
Cited By
Investigating the efficacy of inventory policy implementation in selected state-owned enterprises in the Gauteng province: A qualitative study
Journal of Transport and Supply Chain Management
https://doi.org/10.4102/jtscm.v15i0.552