Routing For Taxi-pooling Problem Based on Ant Colony Optimization Algorithm

Abstract

With the increasingly global environmental awareness, the city transportation strategy tends to be low-carbon and energy-saving. The most focuses of this trend is intelligent transportation. As a supplementary transportation tools between private transportation and public transportation, taxis have been the useful complement of the city public transportation system. The low-carbon and energy-saving way for taxis is called taxipooling. In this work, we focus on the routing problem of taxi-pooling. Specifically, with the analysis of the taxi-pooling problem, we investigate the characteristics and restraints, and construct an optimization model which aims to minimize the cost of passengers, maximize the benefit of drivers and maximize the load rate. To solve the above model, we propose to employ a modified Ant Colony Optimization (ACO) model. Our simulation results show that our method can effectively solve the taxi-pooling routing problem with the above three objectives.