Optimal taxi fleet management: a linear programming approach to the taxi capacity problem

This paper develops a model to determine the optimal number of taxis in a city by examining the trade-off between the overall profitability of the taxi service versus the customer satisfaction. We provide a data analytic investigation of taxi trips in New York City. We model the taxi service strategy by a fleet management model that can handle arrivals and deterministic travel times. Under this model, we examine the number of taxis in a particular period of time and measure the maximum profit in the overall system and the minimum number of rejected customer requests. We observe that the maximum profit of the overall system can be reduced significantly due to reducing the cost of driving without passenger(s). We present a case study with New York City Taxi data with several experimental evaluations of our model with a different period of time during the day and also with a realistic and a heuristic model. The results provide a better understanding of the requirement to satisfy the demand in a different period of time. These data may have important implications in the field of self-driving vehicles in the near future.