Car rental revenue optimization by using the improvement opportunity

Abstract

In the thesis, the application of revenue management in the context of car rental business is introduced. In the reality, the arrival request is uncertainty over time, the operator is not aware of the future request. As the result, it is very hard to accept or reject the current request. In particular, the customer makes a request of car rental, given the car type, length of rent as well as the starting time. When the request arrives, the car rental company will satisfy the customer request. Based on the acceptance policy of company, the operator will accept the request or reject it and propose another car belonging the superior group. It calls upgrade. For this purpose, the model of approximation liner programming is introduced. Because the demand is uncertainty in the reality, the model will be implemented with the dynamic way. Besides the revenue-based opportunity cost acceptance policy is also proposed and their effectiveness is derived by comparing between opportunity cost and first come first serve. Keywords: revenue management, car rental optimization, approximation linear programming, dynamic programming, opportunity cost