A nonlinear mixed-integer programming model for forward/reverse distribution network design

Distribution affects a firm's cost and customer satisfaction and drives profitability. Besides, due to the implementation of government legislation, companies have been required not only to supply environmentally amicable products but also to be responsible for the returned goods. Therefore, in...

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Bibliographic Details
Published in:Chinese Control Conference pp. 2673 - 2677
Main Authors: Liu, Ming, Zhang, Liping
Format: Conference Proceeding Journal Article
Language:English
Published: TCCT 01.07.2016
Subjects:
Conferences
Distribution network design
Environmental legislation
Forward/reverse logistics
Genetic algorithm
Genetic algorithms
Governments
Location
Logistics
Mathematical model
Networks
Nonlinearity
Optimization
Programming
Reverse logistics
Supply chains
Transportation
ISSN:1934-1768
Online Access:Get full text
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Summary:Distribution affects a firm's cost and customer satisfaction and drives profitability. Besides, due to the implementation of government legislation, companies have been required not only to supply environmentally amicable products but also to be responsible for the returned goods. Therefore, in this paper, we present a nonlinear mixed-integer programming model for a forward/reverse logistics network design, with an emphasis on minimizing the total distribution costs. Specifically, the model addresses the following four issues: (1) determine the optimal number of regional distribution centers (RDC); (2) identify where the RDCs should be located; (3) determine the capacity size of each RDC; (4) determine the total distribution costs. A genetic algorithm is developed to solve the model. The test results give important insight for fostering the decision making process.
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ISSN:1934-1768
DOI:10.1109/ChiCC.2016.7553769