Developing lean and responsive supply chains: A robust model for alternative risk mitigation strategies in supply chain designs

被引:70
作者
Mohammaddust, Faeghe [1 ]
Rezapour, Shabnam [2 ]
Farahani, Reza Zanjirani [3 ]
Mofidfar, Mohammad [4 ]
Hill, Alex [3 ]
机构
[1] Urmia Univ Technol, Dept Ind Engn, Orumiyeh, Iran
[2] Univ Oklahoma, Sch Ind & Syst Engn, Norman, OK 73019 USA
[3] Univ Kingston, Kingston Business Sch, Dept Management, Kingston Hill, Kingston Upon Thames KT2 7LB, Surrey, England
[4] Case Western Reserve Univ, Dept Macromol Sci & Engn, Cleveland, OH 44106 USA
关键词
Supply chain management; Network design; Risk management; Robust optimization; Responsiveness; CONTINUUM APPROXIMATION APPROACH; STOCHASTIC-PROGRAMMING APPROACH; FACILITY LOCATION DESIGN; NETWORK DESIGN; SERVICE LEVEL; OPTIMIZATION MODEL; LOGISTICS NETWORKS; DISRUPTION; UNCERTAINTY; DEMAND;
D O I
10.1016/j.ijpe.2015.09.012
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper investigates how organization should design their supply chains (SCs) and use risk mitigation strategies to meet different performance objectives. To do this, we develop two mixed integer nonlinear (MINL) lean and responsive models for a four-tier SC to understand these four strategies: i) holding back-up emergency stocks at the DCs, ii) holding back-up emergency stock for transshipment to all DES at a Straregic DC (for risk pooling in the SC), iii) reserving excess capacity in the facilities, and iv) using other facilities in the SC's network to back-up the primary facilities. A new method for designing the network is developed which works based on the definition of path to cover all possible disturbances. To solve the two proposed MINL models, a linear regression approximation is suggested to linearize the models; this technique works based on a piecewise linear transformation. The efficiency of the solution technique is tested for two prevalent distribution functions. We then explore how these models operate using empirical data from an automotive SC. This enables us to develop a more comprehensive risk mitigation framework than previous studies, and show how it can be used to determine the optimal SC design and risk mitigation strategies given the uncertainties faced by practitioners and the performance objectives they wish to meet. Crown Copyright (C) 2015 Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:632 / 653
页数:22
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