Please use this identifier to cite or link to this item: https://doi.org/10.1155/2018/4390480
Title: Improved Simulated Annealing Based Network Model for E-Recycling Reverse Logistics Decisions under Uncertainty
Authors: Wang, L.
Goh, M. 
Ding, R.
Mishra, V.K. 
Issue Date: 2018
Publisher: Hindawi Limited
Citation: Wang, L., Goh, M., Ding, R., Mishra, V.K. (2018). Improved Simulated Annealing Based Network Model for E-Recycling Reverse Logistics Decisions under Uncertainty. Mathematical Problems in Engineering 2018 : 4390480. ScholarBank@NUS Repository. https://doi.org/10.1155/2018/4390480
Rights: Attribution 4.0 International
Abstract: Electronic waste recycle (e-recycling) is gaining increasing importance due to greater environmental concerns, legislation, and corporate social responsibility. A novel approach is explored for designing the e-recycling reverse logistics network (RLN) under uncertainty. The goal is to obtain a solution, i.e., increasing the storage capacity of the logistics node, to achieve optimal or near-optimal profit under the collection requirement set by the government and the investment from the enterprise. The approach comprises two parts: A matrix-based simulation model of RLN formed for the uncertainty of demand and reverse logistics collection which calculates the profit under a given candidate solution and simulated annealing (SA) algorithm that is tailored to generating solution using the output of RLN model. To increase the efficiency of the SA algorithm, network static analysis is proposed for getting the quantitative importance of each node in RLN, including the static network generation process and index design. Accordingly, the quantitative importance is applied to increase the likelihood of generating a better candidate solution in the neighborhood search of SA. Numerical experimentation is conducted to validate the RLN model as well as the efficiency of the improved SA. © 2018 Lei Wang et al.
Source Title: Mathematical Problems in Engineering
URI: https://scholarbank.nus.edu.sg/handle/10635/209677
ISSN: 1024-123X
DOI: 10.1155/2018/4390480
Rights: Attribution 4.0 International
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