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The Network Optimization for Reverse Logistics under Grey Environment

Author: YuJia
Tutor: BaiMingGuo
School: Anhui University of
Course: Technology Economics and Management
Keywords: Reverse Logistics Network design Grey Planning And other rights albino Genetic Algorithms
CLC: F224
Type: Master's thesis
Year: 2011
Downloads: 132
Quote: 1
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Abstract

1990s, the deterioration of the economic development and the living environment of human conflicts intensified between the scarcity of natural resources, in this context, reverse logistics as an effective to achieve sustained economic development and optimal use of resources, environmental protection integrated target logistics form of logistics concepts appear, and was adopted by many well-known enterprises and take advantage of, and a growing number of scholars and research institutions are also continuous research and exploration of reverse logistics. In reverse logistics, reverse logistics network optimization design is the most fundamental problem of reverse logistics system design, and has a strategic importance in the management of reverse logistics. Compared with conventional logistics network, the reverse logistics network has a high degree of uncertainty makes the network more complexity, it is necessary to carry out in-depth study. In this paper, the uncertainty of the reverse logistics network, research reverse logistics network optimization design problem in the gray environment. Summarizes basis at home and abroad on reverse logistics network optimization literature, first introduced reverse logistics and reverse logistics network, followed by in-depth quantitative research, the following two parts: gray environment re-use of the reverse logistics network optimization design problems. First clear and then take advantage of the characteristics of reverse logistics network design, on this basis, combined with gray gray system theory planning method reuse reverse logistics network design model with gray numbers to express some of the parameters of the network, the use of gray albino gray programming model into the the deterministic equivalence class model, and last through the design of a hybrid intelligent algorithm combined genetic algorithm and the traditional optimization algorithms to solve the model, to determine the number and location of facilities in the logistics network, and thus constitute various logistics paths allocated on a reasonable amount of logistics, so that the cost of investment and operating costs and minimum; the gray environment remanufacturing reverse logistics network optimization design problem. First clear remanufacturing reverse logistics network design characteristics, remanufacturing reverse logistics network design model established planning method based on gray system theory, gray, on this basis, and considering the uncertainties gray parameters through the of gray parameters whitening process, the model is transformed to determine the type of the equivalence class model, and finally by the optimization software to solve the model, to determine the number and location of the facilities in the logistics network, and on the various logistics path thereby constituting reasonable distribution logistics quantity to make The cost of the investment and operating costs and minimum.

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