Title: Multi-objective optimisation for taxi ridesharing route based on non-dominated sorting genetic algorithm

Authors: Qing Ye; Changxi Ma; Ruichun He; Qiang Xiao; Wei Zhang

Addresses: School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou, 730070, China

Abstract: The paper was aimed to design a method to optimise the taxi ridesharing routes. Firstly, the paper built the objective function to minimise the total ridesharing fare of passengers, the total ridesharing travelling time of passengers and the total fuel charge of taxies under the constraints of driver's income, the travelling fare of passenger, the fuel charge of taxi and established the route optimisation model for taxi rideshare. Secondly, the paper designed non-dominated sorting genetic algorithm to solve the model. Finally, the part road network of Lanzhou Chengguan district was taken as an example for case analysis. The results show that the ridesharing routes can be obtained quickly by using the route optimisation model and algorithm and adopting the ridesharing routes can increase the income of taxi drivers as well as reduce the travelling fare of the passenger.

Keywords: non-dominated sorting genetic algorithms; NSGA; taxi ridesharing; taxis; multi-objective optimisation; passenger fares; taxi fares; travelling time; driver income; fuel charges; route optimisation; ridesharing routes; taxi sharing.

DOI: 10.1504/IJWMC.2015.069409

International Journal of Wireless and Mobile Computing, 2015 Vol.8 No.3, pp.262 - 270

Received: 20 Dec 2014
Accepted: 13 Jan 2015
Published online: 14 May 2015 *

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