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Dynamic Vehicle Routing Problems with Enhanced Ant Colony Optimization
Joint Authors
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-02-15
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
As we all know, there are a great number of optimization problems in the world.
One of the relatively complicated and high-level problems is the vehicle routing problem (VRP).
Dynamic vehicle routing problem (DVRP) is a major variant of VRP, and it is closer to real logistic scene.
In DVRP, the customers’ demands appear with time, and the unserved customers’ points must be updated and rearranged while carrying out the programming paths.
Owing to the complexity and significance of the problem, DVRP applications have grabbed the attention of researchers in the past two decades.
In this paper, we have two main contributions to solving DVRP.
Firstly, DVRP is solved with enhanced Ant Colony Optimization (E-ACO), which is the traditional Ant Colony Optimization (ACO) fusing improved K-means and crossover operation.
K-means can divide the region with the most reasonable distance, while ACO using crossover is applied to extend search space and avoid falling into local optimum prematurely.
Secondly, several new evaluation benchmarks are proposed, which can objectively and comprehensively estimate the proposed method.
In the experiment, the results for different scale problems are compared to those of previously published papers.
Experimental results show that the algorithm is feasible and efficient.
American Psychological Association (APA)
Xu, Haitao& Pu, Pan& Duan, Feng. 2018. Dynamic Vehicle Routing Problems with Enhanced Ant Colony Optimization. Discrete Dynamics in Nature and Society،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1152257
Modern Language Association (MLA)
Xu, Haitao…[et al.]. Dynamic Vehicle Routing Problems with Enhanced Ant Colony Optimization. Discrete Dynamics in Nature and Society No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1152257
American Medical Association (AMA)
Xu, Haitao& Pu, Pan& Duan, Feng. Dynamic Vehicle Routing Problems with Enhanced Ant Colony Optimization. Discrete Dynamics in Nature and Society. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1152257
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1152257