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A parallel Ant Colony System based on region decomposition for Taxi-Passenger Matching

Authors
Situ, XinChen, Wei-NengGong, Yue-JiaoLin, YingYu, Wei-JieYu, ZhiwenZhang, Jun
Issue Date
Jul-2017
Publisher
Institute of Electrical and Electronics Engineers Inc.
Keywords
Ant colony system (ACS); Region-dependent decomposition (RDD); Taxi dispatch; Taxi-Passenger Matching (TPM)
Citation
2017 IEEE Congress on Evolutionary Computation (CEC), pp 960 - 967
Pages
8
Indexed
SCI
SCOPUS
Journal Title
2017 IEEE Congress on Evolutionary Computation (CEC)
Start Page
960
End Page
967
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/116351
DOI
10.1109/CEC.2017.7969412
Abstract
Taxi dispatch is a critical issue for taxi company to consider in modern life. This paper formulates the problem into a taxi-passenger matching model and proposes a parallel ant colony optimization algorithm to optimize the model. As the search space is large, we develop a region-dependent decomposition strategy to divide and conquer the problem. To keep the global performance, a critical region is defined to deal with the communications and interactions between the subregions. The experimental results verify that the proposed algorithm is effective, efficient, and extensible, which outperforms the traditional global perspective greedy algorithm in terms of both accuracy and efficiency. © 2017 IEEE.
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