Title: Comparison of single-echelon vs. multi-echelon inventory systems using multi-objective stochastic modelling

Authors: Nadeera Ekanayake; Nilesh Joshi; Shital A. Thekdi

Addresses: Engineering and Technology Management, Morehead State University, Morehead, KY 40351, USA ' Engineering and Technology Management, Morehead State University, 201 Lloyd Cassity Bldg, 4th St., Morehead, KY 40351, USA ' Robins School of Business, University of Richmond, VA 23173, USA

Abstract: Recent advancements in inventory management have identified need for investigating benefits of single-echelon and multi-echelon systems. Single-echelon inventory control problems focus on determining the appropriate level of inventory for an individual unit within the supply chain network, while multi-echelon inventory optimisation takes a holistic approach by focusing on the correct levels of inventory across the entire network. This paper presents a stochastic modelling approach for multi-tier supply chains with multiple inventory items. The approach will be used to compare behaviour of single-echelon vs. multi-echelon inventory systems. A multi-objective optimisation method is used to optimise model's behaviour with two conflicting objectives: minimising average inventory across the supply chain and maximising overall fill rate. The results show that single-echelon systems result in higher inventory levels and lower fill rates, while multi-echelon systems result in lower inventory levels while maintaining higher fill rates for the entire supply chain network. The methods are demonstrated on a sample network database.

Keywords: single-echelon inventory systems; multi-echelon inventory systems; distribution; logistics; optimisation; stochastic modelling; inventory management; inventory control; supply chain management; SCM; fill rate; inventory levels; supply networks.

DOI: 10.1504/IJLSM.2016.073971

International Journal of Logistics Systems and Management, 2016 Vol.23 No.2, pp.255 - 280

Received: 15 Sep 2014
Accepted: 19 Oct 2014
Published online: 31 Dec 2015 *

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