Impact of assignment, inventory policies and demand patterns on supply chain performance

T. Al-Hawari, A. Ahmed, S. Khrais, A. Mumani

Research output: Contribution to journalReview articlepeer-review

10 Scopus citations


A simulation model is built to analyse the performance of a four-level/three-product supply chain composed of a retailer, distributor, manufacturer and supplier. The effects of assignment policies; preferred, cyclical and random, were analysed in combination with various factors such as inventory policies; continuous review (r, Q) and periodic review (T, S), and different demand patterns. On-hand inventory and percentage of satisfied customers at various levels of the SC are used as key performance indicators. In (T, S) systems, it is found that imposing an upper limit on S in some SC levels due to the assumption that an order is shipped as a whole in one trip would greatly influence results. Consequently, an increase in T not associated with a sufficient increase in S would decrease inventory levels that would lead to shortages between orders. In (r, Q) systems, the results show clearly how the effect of increasing Q in one level is transformed to upstream and downstream levels. Upstream levels are all negatively affected, while downstream levels maintain the same levels of inventory without any noticeable trends. ANOVA results show that at low demand rates inventory policies are the most significant, then demand patterns while the assignment policies are mostly insignificant. At high demand rates the assignment policy factor becomes significant as well as the other two factors. Sensitivity analysis performed shows the robustness of the results under varying conditions.

Original languageEnglish (US)
Pages (from-to)164-177
Number of pages14
JournalInternational Journal of Simulation Modelling
Issue number3
StatePublished - Sep 2013
Externally publishedYes

Bibliographical note

Copyright 2013 Elsevier B.V., All rights reserved.


  • Assignment policies
  • Inventory policies
  • Simulation
  • Supply chain management


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