Abstract
This paper describes a dynamic model of profit maximization for a car-sharing system, taking into consideration the geographical and economic characteristics of a region. To solve the model construction task, a technique to cover the region with geometric shapes has been described. It was established that when modeling a car-sharing system, it is rational to cover a region with a grid of equal regular hexagons located side to side. For each subregion, quantitative parameters were calculated: the number of free cars in the subregions, the probability of a car traveling from one sub-region to another, the cost of maintenance and operation of the car, and the income from the trip. This takes into consideration the dynamic nature of the specified parameters. Based on these parameters, an objective function is constructed including constraints for the dynamic model. These constraints take into consideration the economic and geographical features of each subregion. A dynamic profit maximization model was built for the car-sharing system in the city of New York (USA) based on the TCL dataset. To calculate the parameters of the model, data on 776,285,070 trips over the period from January 2016 to July 2021 were used. Maps of the beginning and completion of trips in the region and a map of trips tied to hexagonal grid cells using the Kepler visualization service have been built. The frameworks H3 and S2 were analyzed in terms of determining the length of the route between the subregions. Modeling was carried out according to the built unidirectional dynamic model of profit maximization. It has been established that taking into consideration the average economic and geographical characteristics of a region makes it possible to increase the profit of the car-sharing system by 12.36 %. Accounting for the dynamics of economic and geographical features of the region of customers in the model makes it possible to increase profits by an additional 4.18 %
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