Improved Simulated Annealing Based Network Model for E-Recycling Reverse Logistics Decisions under Uncertainty
Joint Authors
Wang, Lei
Goh, Mark
Ding, Ronggui
Mishra, Vikas Kumar
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-18
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Wang, Lei& Goh, Mark& Ding, Ronggui& Mishra, Vikas Kumar. 2018. Improved Simulated Annealing Based Network Model for E-Recycling Reverse Logistics Decisions under Uncertainty. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-17.
https://search.emarefa.net/detail/BIM-1207464
Modern Language Association (MLA)
Wang, Lei…[et al.]. Improved Simulated Annealing Based Network Model for E-Recycling Reverse Logistics Decisions under Uncertainty. Mathematical Problems in Engineering No. 2018 (2018), pp.1-17.
https://search.emarefa.net/detail/BIM-1207464
American Medical Association (AMA)
Wang, Lei& Goh, Mark& Ding, Ronggui& Mishra, Vikas Kumar. Improved Simulated Annealing Based Network Model for E-Recycling Reverse Logistics Decisions under Uncertainty. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-17.
https://search.emarefa.net/detail/BIM-1207464
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1207464