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To fully take the advantages of ride-sharing ride hailing, such as high loading rate, high operating efficiency, and less traffic resources, and to alleviate the difficulty of getting a taxi in urban hubs, the topic of ride-sharing route optimization for ride hailing is studied in this paper. For the multiple ride hailing ride-sharing demands and multiple ride hailing services in the urban road network in a specific period, the objective function is established with the shortest route of the system. The constraint conditions of the optimization model are constructed by considering factors of the rated passenger capacity, route rationality, passenger benefits, driver benefits and time window. Based on the idea of the Genetic Algorithm, the solution algorithm of the optimization model is developed. According to the supply and demand data of taxi during peak hours in the local road network in the city of Dalian, the optimization model and algorithm are used to optimize the ride-sharing route scheme. Research results indicate that the optimization model and algorithm can find the approximate optimal solution of the system in a short time. Compared with the traditional non-ride-sharing mode, the ride-sharing scheme can not only effectively reduce the taxi empty-loaded rate and the travel cost of passengers, improve the efficiency of drivers, but also save energy and reduce emissions, and promote the sustainable development of urban traffic.

The Optimization Model of Ride-Sharing Route for Ride Hailing Considering Both System Optimization and User Fairness