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An Efficient Algorithm for Taxi System Optimization


Authors: J. Gan, B. An, and C. Miao
Title: An Efficient Algorithm for Taxi System Optimization
Abstract: Taxi service is an important mode of modern public transportation. However, operated by a large number of self-controlled and profit-driven taxi drivers, taxi systems are quite in efficient and difficult to analyze and regulate. While there has been some work on designing algorithms for improving taxi system efficiency, the state of the art algorithm, unfortunately, cannot scale up efficiently. To address the inadequacy, we propose a novel algorithm—FLORA—in this paper. Using convex polytope representation conversion techniques, FLORA provides a fully compact representation of taxi drivers’ strategy space, and avoids enumerating any type of schedules. Experimental results show orders of magnitude improvement of FLORA in terms of the complexity.
Keywords: Taxi system; Game theory; Optimization
Conference Name: 13th International Conference on Autonomous Agents and Multi-agent Systems (AAMAS’14)
Location: Paris, France
Publisher: IFAAMAS
Year: 2014
Accepted PDF File: 
Permanent Link: http://aamas2014.lip6.fr/proceedings/aamas/p1465.pdf
Reference: J. Gan, B. An, and C. Miao, “An efficient algorithm for taxi system optimization,” in Proceedings of the 13th International Conference on Autonomous Agents and Multi-agent Systems (AAMAS’14). IFAAMAS, May 2014, pp. 1465–1466.
bibtex: 
@inproceedings{LILY-c18, 
   author	= {Gan, Jiarui and An, Bo and Miao, Chunyan},
   title	= {An Efficient Algorithm for Taxi System Optimization},  
   booktitle	= {Proceedings of the 13th International Conference on Autonomous Agents and Multi-agent Systems (AAMAS'14)}, 
   year		= {2014}, 
   month	= {May}, 
   pages	= {1465-1466}, 
   location	= {Paris, France},
   publisher	= {IFAAMAS},
}