Research on ride-sharing taxi model optimization and routing choice based on the genetic algorithm

Ride-sharing is not a strange word and it is rising gradually in a number of small and medium-sized cities. Some theses have studied ride-sharing, model building and cost-sharing. With environmental issues increasingly becoming a topic of concern, how to reduce the environmental impact of a taxi, reduce passengers’ costs and increase drivers’ or the entire industry’s revenue, there are that many researchers continue to explore these aspects of the application. Graph theory model of ride-sharing taxi system can illustrate the problem to a certain extent. However, there are a number of differences with the real system, and the discrepancy considering the income of taxi drivers. Based on the researches of others, the authors enrich and improve the taxi ride-sharing taxi model, regard the average income of taxi drivers, the average costs of passengers as well as the overall effect of social as the goal of ride-sharing taxi model, modify the model constraints and make the model more realistic. Finally, the time window is introduced to simulate the taxi passenger travel time, location, number and route like passengers in real system, and genetic algorithm is used to solve the model with time windows by Matlab10. From a computational experiment which is solved by using refined model, the value and benefits of ride-sharing taxi will be gained. So the ride-sharing taxi has an effect on the mitigation of urban traffic congestion and resource-wasting, which can not only help raise the city's road service levels, and reduce the total passengers’ travel distance, thereby reducing the environmental pollution.