DocumentCode :
162655
Title :
Online taxi sharing optimization using evolutionary algorithms
Author :
Fagundez, Gabriel ; Massobrio, Renzo ; Nesmachnow, Sergio
Author_Institution :
Centro de Calculo, Univ. de la Republica, Montevideo, Uruguay
fYear :
2014
fDate :
15-19 Sept. 2014
Firstpage :
1
Lastpage :
12
Abstract :
This article presents the application of evolutionary algorithms for solving the problem of distributing a group of passengers travelling from the same origin to different destinations in several taxis, with the goal of minimizing the total cost of the trips. The experimental analysis compares the quality of the solutions found using the proposed algorithm versus those computed using an intuitive greedy heuristic similar to those previously proposed in the related literature to solve the problem, showing that the evolutionary algorithm is able to reach significant improvements in the trips´ total cost, outperforming the greedy heuristic in up to 41.7 % in the best case, and up to 36.4% on average. Two applications are also presented: a web-based user interface and a mobile application for devices using the iOS operating system.
Keywords :
Internet; evolutionary computation; iOS (operating system); mobile computing; optimisation; traffic engineering computing; user interfaces; Web-based user interface; evolutionary algorithms; iOS operating system; mobile application; online taxi sharing optimization; passenger distribution; Algorithm design and analysis; Computational modeling; Electronic mail; Evolutionary computation; Global Positioning System; Optimization; Silicon compounds;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing Conference (CLEI), 2014 XL Latin American
Conference_Location :
Montevideo
Type :
conf
DOI :
10.1109/CLEI.2014.6965163
Filename :
6965163
Link To Document :
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