Multi-depots distribution problem study based on rich network road model

The multi-depots distribution logistic is a particular combination of transportation and routing problems, in which items that have to be loaded into different customers within vehicles, and then delivered with minimum cost. In this paper, a model is built firstly and the weights between the target...

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Bibliographic Details
Published in2013 25th Chinese Control and Decision Conference (CCDC) pp. 875 - 880
Main Authors Chunlong Yao, Guijun Zhang, Beijin Zhang, Siheng Zhong
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2013
Subjects
Classification algorithms
dijkstra algorithm
Heuristic algorithms
Linear programming
Logistics
path optimal
rich network model
Roads
Support vector machine classification
time optimal
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Summary:The multi-depots distribution logistic is a particular combination of transportation and routing problems, in which items that have to be loaded into different customers within vehicles, and then delivered with minimum cost. In this paper, a model is built firstly and the weights between the target nodes are acquired based on actual network road by branch-and-cut and Dijkstra algorithms; Next, the idea of the evolutionary tree classification is used to solve the nonlinear cost variables in the distribution model. Extensive computational results show that the proposed algorithm are capable of solving to optimality for a large number of small-size instances, and consistently outperform previous algorithms from the literature on large-size and real-world instances.
ISBN:9781467355339
146735533X
ISSN:1948-9439
1948-9447
DOI:10.1109/CCDC.2013.6561046