Title: Development of a multi-period model to minimise logistic costs and maximise service level in a three-echelon multi-product supply chain considering back orders
Authors: Ashkan Hafezalkotob; Kaveh Khalili-Damghani
Addresses: Department of Industrial Engineering, Faculty of Industrial Engineering, South-Tehran Branch, Islamic Azad University, Tehran, Iran ' Department of Industrial Engineering, Faculty of Industrial Engineering, South-Tehran Branch, Islamic Azad University, Tehran, Iran
Abstract: In this paper, a multi-objective multi-period supply chain design and planning problem is introduced. The problem seeks to minimise logistic costs and maximise service level in a three-echelon multi-product supply chain considering back orders. The layers of chain include suppliers, manufacturers and distribution centres. The parts of logistic costs are discussed and modelled while service level is also interpreted as low level of backorder and shortening the delivery time of products to customers. This problem is modelled using a multi-objective mixed integer mathematical programming. Several constraints due to real-world conditions are also considered in the proposed model. As the objective functions, i.e., logistic costs and satisfaction levels are conflictive so a posteriori multi-objective mathematical approach, called efficient epsilon-constraint is proposed to generate several non-dominated solutions on Pareto front of the problem. Illustrated numerical example is solved using proposed approach in order to demonstrate the efficacy and applicability of proposed model and the solution procedure.
Keywords: logistics planning; supply chain management; SCM; supply networks; network planning; multi-objective optimisation; efficient epsilon constraint; EEC; multi-period models; logistics costs; service levels; back orders; modelling.
DOI: 10.1504/IJADS.2015.069599
International Journal of Applied Decision Sciences, 2015 Vol.8 No.2, pp.145 - 163
Received: 12 Sep 2014
Accepted: 12 Nov 2014
Published online: 28 May 2015 *