A Complex Design of the Integrated Forward-Reverse Logistics Network under Uncertainty
Publish place: International Journal of Industrial Engineering & Production Research، Vol: 23، Issue: 2
Publish Year: 1391
نوع سند: مقاله ژورنالی
زبان: English
View: 849
This Paper With 12 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_IJIEPR-23-2_005
تاریخ نمایه سازی: 7 شهریور 1393
Abstract:
Design of a logistics network in proper way provides a proper platform for efficient and effective supply chain management. This paper studies a multi-period, multi echelon and multi-product integrated forward-reverse logistics network under uncertainty. First, an efficient complex mixed-integer linear programming (MILP) model by considering some real-world assumptions is developed for the integrated logistics network design to avoid the sub-optimality caused by the separate design of the forward and reverse networks. Then, the stochastic counterpart of the proposed MILP model is used to measure the conditional value at risk (CVaR) criterion, as a risk measure, that can control the risk level of the proposed model. The computational results show the power of the proposed stochastic model with CVaR criteria in handling data uncertainty and controlling risk levels.
Keywords:
Conditional value at risk (CVaR) , Closed-loop logistics , Stochastic programming , Supply chain management
Authors
R. Babazadeh
is M.S. Student in Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.
R. Tavakkoli-Moghaddam
is a Professor in Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.
J. Razmi
is an Associate Professor in Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.