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عنوان فارسی مقاله:

یک رویکرد پیشگیرانه برای مدیریت ریسک زنجیره تامین: تغییر در سفارشات در میان تامین کنندگان برای کاهش ریسک عرضه


عنوان انگلیسی مقاله:

A proactive approach to supply chain risk management: Shifting orders among suppliers to mitigate the supply side risks


سال انتشار : 2016



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بخشی از مقاله انگلیسی:


2. Literature review Effective mathematical tools for analyzing and understanding appropriate supply chain risk management are attracting much attention due to increasing interest on supply chain vulnerabilities. Although the studies on supply chain risk management are mostly qualitative and empirical, there are also qualitative and modelbased researches in literature. For example; Arntzen et al. (1995) implemented a mixed integer programming model that is used for determining optimal supplier relationship, optimal supply network design, optimal supplier order allocation and optimal supply contract. Camm et al. (1997) propose an integer programming model for Proctor and Gamble that deals with supply network design and supplier selection. Levy (1995) presents a simulation model to examine the impact of demand uncertainty and supplier reliability on the performance of different supply networks and supply contracts. Lee and Tang (1998a, 1998b) propose a stochastic inventory model to examine the tradeoff between the consignment and turnkey arrangements under demand uncertainty (Tang, 2006). Kouvelis and Rosenblatt (2002) have studied the design of global facility networks and presented a mixed integer programming model. They investigate essential design tradeoffs of such networks and incorporate government subsidies trade tariffs and taxation issues. Smith and Huchzermeier (2003) have studied the global supply chain and risk optimization, and showed how real options add value to global manufacturing firms (Goh et al., 2007). Bogataj and Bogataj (2007) develop a parametric linear programming approach for measuring supply chain risks in terms of lead time perturbations. Mark et al. (2007) present a stochastic model of the multi-stage global supply chain network problem, incorporating a set of related risks as supply, demand, exchange and disruption. The firm’s objective is to maximize its global after-tax profit subject to capacity constraints in each plant and demand requirements in each market. Hopp and Yin (2006) used a nonlinear mixed integer programming (NLMIP) formulation to explain supply disruption caused by catastrophic failure. The aim of the study is minimizing total cost comprising of inventory and protection costs. Effects of several different protection policies were analyzed for mitigating disruption risks. Buffa and Jackson (1983) used multi-objective mathematical programming to model a supplier selection problem. Wadhwa and Ravindran (2007) developed a three-criterion mathematical model to select suppliers with capacity constraints. Xia and Wu (2007) developed a fourobjective mixed integer formulation for supplier selection under volume price discounts. Bundschuh et al. (2003) used an NLMIP model to investigate reliability and robustness in supply chains. Sodhi (2005) presents two risk measures for demand risk and inventory risk. He has proposed two linear programming models to manage demand and inventory risk in a consumer electronics supply chain.

 


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کلمات کلیدی:

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