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An Integrated Strategy for Cost Optimization of Reverse Logistics Network Under Uncertain Environment
International Journal of Economics, Finance and Management Sciences
Volume 5, Issue 1, February 2017, Pages: 24-33
Received: Oct. 19, 2016; Accepted: Nov. 7, 2016; Published: Dec. 29, 2016
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Authors
Yunzhi Ma, College of Computer and Information Technology, China Three Gorges University, Yichang, China
Liyun Zhang, College of Economics and Management, China Three Gorges University, Yichang, China
Xianglin Lv, College of Computer and Information Technology, China Three Gorges University, Yichang, China
Zhengying Cai, College of Computer and Information Technology, China Three Gorges University, Yichang, China
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Abstract
In uncertain environment, it is very difficult to optimize both cost and performance in complex reverse logistics network. This paper develops an integrated strategy to solve the cost optimization problem in reverse logistics network. First, the integrated scheme is based on the fuzzy AHP, where the cost coefficient and the demand quantities are modeled as fuzzy numbers to measure different uncertain factors. Second, the linear programming is introduced for cost optimization to calculate the operational objective function of the reverse logistics network. Third, some experiments are made to verify the proposed model. According to different uncertain factors, the optimal cost strategy can be constructed for uncertain use demand. Last, some interesting conclusions are drawn on the proposed method for decision makers to optimize the cost of the reverse logistics network, and future work direction is also provided.
Keywords
Reverse Logistics Network, Cost Optimization, Fuzzy AHP, Linear Programming
To cite this article
Yunzhi Ma, Liyun Zhang, Xianglin Lv, Zhengying Cai, An Integrated Strategy for Cost Optimization of Reverse Logistics Network Under Uncertain Environment, International Journal of Economics, Finance and Management Sciences. Vol. 5, No. 1, 2017, pp. 24-33. doi: 10.11648/j.ijefm.20170501.13
Copyright
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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