Ride-hailing Scheduling Study Based On Platform Economics

In recent years,with the rapid development of mobile and wireless communication technologies,various ride-hailing platforms,like Didi,Uber.Ola Cabs,have become popular worldwide.The convenient and fast information exchange of the ride-hailing platforms greatly alleviates the information barrier caused by the space-time deviation between passengers and drivers in the traditional taxi system,and makes the ride-hailing platforms becoming a powerful tool to improve the efficiency of the taxi market.The scheduling scheme of the ride-hailing platforms directly affects the platforms' operating profit and the ride-hailing users' trip utility.The existing ride-hailing platforms have two main scheduling modes:order grabbing and order dispatching.Compared with the grab mode,the dispatch mode sacrifices the freedom of drivers,but it can consider the supply and demand relationship in the whole taxi market as well as the matching degree between passengers and drivers,which is conducive to improving the whole scheduling efficiency.Based on this,this paper mainly studies the scheduling problem of ride-hailing platform under the dispatch mode.In this paper,we use literature review,news collection and other methods to understand the operation mode,pricing rules,users' costs and the profit of ride-hailing platforms,and the expression method of passengers and drivers' trip utility and the calculation formula of operating profit of the platform are given.In addition,according to whether the vehicle is idle or not,we divide the vehicle drivers into two categories:empty drivers and non-empty drivers,and divides the non-empty drivers into two states:available and unavailable.On this basis,we first established a nonlinear mixed integer programming model under the ride-hailing platform's dispatch mode,aiming at maximizing the platform's operating profit,and taking into account the users' trip utility and the availability of non-empty drivers.Considering that it is difficult to solve the nonlinear model with existing software directly,this paper introduces the linearized reconstruction technology,which is used to transform the nonlinear model into a linear model that can be directly solved,then we give the simple proof of the transformation constraints to ensure the feasibility of the transformation process.Mixed integer linear programming model can use CPLEX to solve directly,this paper introduces the mechanism of CPLEX,and caused by that CPLEX takes too long time to solve large-scale problems with a large number of integer variables,we design a heuristic algorithm based on variable neighborhood search to solve this ride-hailing scheduling problem Then,according to relevant operation data of Didi private car(starting price,mileage fee,etc.),relevant example parameters are set,and two scenarios are designed for case analysis.We first use the CPLEX and the algorithm based on the variable neighborhood search to solve the examples in different scenarios,respectively.We find that the algorithm based on the variable neighborhood search has higher solving efficiency in the large-scale problem and when the non-empty vehicle drivers are available.Then,based on the variable neighborhood search algorithm,we analyze the effects of passenger and driver's size ratio and the availability of non-empty drivers on the platform's total profit,users' trip utility and solution time.We found that for the platform,the greater the ratio of passenger size to driver size,the platform has more opportunity to obtain a better scheduling solution.At the same time,we found that while non-empty drivers are available,the average waiting time of passengers will increase.However,the number of matches between passengers and drivers remains stable,so the platform can obtain higher operating profit.Finally,we systematically summarize the research content of this paper,and prospects the possible research directions in the future.