RENTAL VEHICLE SYSTEM OPTIMIZATION

1 . A system that facilitates navigating a touch screen, comprising:

a memory that stores computer executable components; and

a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise:

a search component that receives a request for a rental vehicle booking from a user identity and identifies available vehicles included in a fleet of rental vehicles that satisfy one or more criteria for the rental vehicle booking included with the request;

a ranking component that ranks the available vehicles according to an estimated preference priority order for the user identity based on different preference profiles of virtual users representing different combinations of preference weightings for the one or more criteria;

a recommendation component that generates an ordered list of the available vehicles to the user identity generated based on the estimated preference priority order; and

a results component that provides the ordered list to the user identity to facilitate selecting one of the available vehicles for booking.

2 . The system of claim 1 , wherein the different preference profiles further represent additional different combinations of preference weightings for additional criteria associated with the available vehicles and the rental vehicle booking.

3 . The system of claim 1 , wherein the ranking component selects a subset of the different preference profiles based on the subset having a defined degree of correspondence to a user profile for the user identity, and wherein the ranking component ranks the available vehicles based on the subset of the different preference profiles.

4 . The system of claim 3 , wherein the user profile for the user identity indicates preference weightings of the user identity for the one or more criteria and additional criteria associated with the available vehicles and the rental vehicle booking, and wherein the computer executable components further comprise:

a preferences component that employs machine learning and artificial intelligence to infer the user profile for the user identity.

5 . The system of claim 1 , wherein the ranking component further ranks the available vehicles according to an estimated preference priority order for the user identity based on a one or more contextual factors associated with the rental vehicle booking.

6 . The system of claim 1 , wherein the ranking component determines individual preference priority orders of the available vehicles for each of the virtual users based on their respective preference profiles of the different preference profiles and determines the estimated preference priority order based on the individual preference priorities orders.

7 . The system of claim 6 , wherein the recommendation component selects a first vehicle of the available vehicles as a first-choice recommendation in the estimated preference priority order that cumulatively received the highest ranking amongst individual preference priority orders.

8 . The system of claim 7 , wherein the recommendation component selects a second vehicle of the available vehicles as a second-choice recommendation in the estimated preference priority order based on the second vehicle having at least one different criterion from the first vehicle.

9 . The system of claim 7 , wherein based on the first vehicle comprising a first value for a dynamic parameter, the recommendation component does not select a second vehicle as a second-choice recommendation if the second vehicle comprises a second value for the dynamic parameter that is considered less favorable than the first value.

10 . The system of claim 9 , wherein the dynamic parameter comprises a distance between a first location of the user identity and a second location of a candidate vehicle of the available vehicles, and wherein the less favorable value corresponds to a greater distance.

11 . The system of claim 9 , wherein the dynamic parameter comprises cost and wherein the less favorable value corresponds to a greater cost.

12 . A method, comprising:

determining, by a system operatively coupled to a processor, available vehicles included in a fleet of rental vehicles that satisfy one or more criteria for a rental vehicle booking included in a request received for the rental vehicle booking from a user identity;

ranking, by the system, the available vehicles according to an estimated preference priority order for the user identity based on different preference profiles of virtual users representing different combinations of preference weightings for the one or more criteria; and

generating, by the system, an ordered list of the available vehicles based on the estimated preference priority order; and

providing, by the system, the ordered list to the user identity to facilitate selecting one of the available vehicles for booking.

13 . The method of claim 12 , wherein the different preference profiles further represent additional different combinations of preference weightings for additional criteria associated with the available vehicles and the rental vehicle booking.

14 . The method of claim 12 , wherein the ranking comprises selecting a subset of the different preference profiles based on the subset having a defined degree of correspondence to a user profile for the user identity, and ranking the available vehicles based on the subset of the different preference profiles.

15 . The method of claim 12 , wherein the ranking comprises determining individual preference priority orders of the available vehicles for each of the virtual users based on their respective preference profiles of the different preference profiles and determining the estimated preference priority order based on the individual preference priorities orders.

16 . The method of claim 15 , wherein the generating comprises selecting a first vehicle of the available vehicles as a first-choice recommendation in the estimated preference priority order that cumulatively received the highest ranking amongst individual preference priority orders.

17 . The method of claim 16 , wherein the generating further comprises selecting a second vehicle of the available vehicles as a second-choice recommendation in the estimated preference priority order based on the second vehicle having at least one different criterion from the first vehicle.

18 . The method of claim 16 , wherein based on the first vehicle comprising a first value for a dynamic parameter and a second vehicle comprising a second value for the dynamic parameter that is considered less favorable than the first value, the generating comprises selecting a third vehicle as a second-choice recommendation in the estimated preference priority order.

19 . A machine-readable storage medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations, comprising:

receiving a request for a rental vehicle booking from a user identity, the request identifying one or more criteria for the rental vehicle booking;

identifying available vehicles included in a fleet of rental vehicles that satisfy the one or more criteria;

ranking the available vehicles according to an estimated preference priority order for the user identity based on different preference profiles of virtual users representing different combinations of preference weightings for the one or more criteria;

generating an ordered list of the available vehicles based on the estimated preference priority order; and

providing the ordered list to the user identity to facilitate selecting one of the available vehicles for booking.

20 . The machine-readable storage medium of claim 19 , wherein the ranking comprises determining individual preference priority orders of the available vehicles for each of the virtual users based on their respective preference profiles of the different preference profiles and determining the estimated preference priority order based on the individual preference priorities orders.