标题:Improved Simulated Annealing Based Network Model for E-Recycling Reverse Logistics Decisions under Uncertainty
作者:Wang, Lei; Goh, Mark; Ding, Ronggui; Mishra, Vikas Kumar
作者机构:[Wang, Lei; Ding, Ronggui] Shandong Univ, Sch Management, Jinan 250100, Shandong, Peoples R China.; [Wang, Lei; Goh, Mark; Mishra, Vikas Kumar] Natl 更多
通讯作者:Ding, Ronggui;Ding, RG
通讯作者地址:[Ding, RG]Shandong Univ, Sch Management, Jinan 250100, Shandong, Peoples R China.
来源:MATHEMATICAL PROBLEMS IN ENGINEERING
出版年:2018
卷:2018
DOI:10.1155/2018/4390480
摘要: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.
收录类别:EI;SCOPUS;SCIE;SSCI
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059504217&doi=10.1155%2f2018%2f4390480&partnerID=40&md5=846d0f8a3df71353e4e4565ff9294110
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