Incorporating location, routing, and inventory decisions in a bi-objective supply chain design problem with risk-pooling

Journal of Industrial Engineering International

دوره 9، شماره 1، اسفند 2013   

نویسندگان

Reza Tavakkoli-Moghaddam^{* 1}؛ Fateme Forouzanfar²؛ Sadoullah Ebrahimnejad³

¹School of Industrial & Systems Engineering and Department of Engineering Science, College of Engineering, University of Tehran, Tehran, Iran

²School of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

³Department of Industrial Engineering, Karaj Branch, Islamic Azad University, Karaj, Iran

چکیده

This paper considers a single-sourcing network design problem for a three-level supply chain. For the first time, a novel mathematical model is presented considering risk-pooling, the inventory existence at distribution centers (DCs) under demand uncertainty, the existence of several alternatives to transport the product between facilities, and routing of vehicles from distribution centers to customer in a stochastic supply chain system, simultaneously. This problem is formulated as a bi-objective stochastic mixed-integer nonlinear programming model. The aim of this model is to determine the number of located distribution centers, their locations, and capacity levels, and allocating customers to distribution centers and distribution centers to suppliers. It also determines the inventory control decisions on the amount of ordered products and the amount of safety stocks at each opened DC, selecting a type of vehicle for transportation. Moreover, it determines routing decisions, such as determination of vehicles' routes starting from an opened distribution center to serve its allocated customers and returning to that distribution center. All are done in a way that the total system cost and the total transportation time are minimized. The Lingo software is used to solve the presented model. The computational results are illustrated in this paper.

کلیدواژه‌ها

Stochastic supply chain؛ Inventory control؛ Risk-pooling؛ Uncertainty؛ Capacity levels