Delivery driver routing and order preparation timing system

1. A system for automated delivery driver routing and order preparation timing, comprising:

an optimization engine comprising a first plurality of programming instructions stored in a memory of, and operable on a processor of, a network-connected computing device, wherein the first plurality of programming instructions, when operating on the processor, cause the computing device to:

receive availability information from one or more mobile devices each associated with a delivery driver, the availability information comprising a driver location, a vehicle type, a vehicle capacity, and routing information for orders currently in the vehicle for delivery, the routing information comprising one or more delivery locations and delivery times;

receive order information from one or more business enterprise computing devices for one or more orders, the order information for each order comprising an order identifier, a business enterprise location, a predicted order preparation time for each order, and a time that the order was placed;

create a data graph from the availability information and the order information, the data graph comprising vertices and edges, wherein the vertices represent data points and the edges represent relationships between the data points;

analyze the data graph to create a schedule for order preparation, pickup, and delivery of each order;

send a pickup request to one or more of the delivery driver mobile devices for each order, the pickup request comprising the order identifier and a time for pickup; and

send a preparation start time to the business enterprise computing device, the preparation start time being calculated such that the order is ready at or before the time for pickup.

2. The system of claim 1 , wherein the availability information further comprises hours of availability of each driver.

3. The system of claim 1 , wherein the availability information further comprises one or more areas of operation of each driver.

4. The system of claim 1 , further comprising a traffic data retriever comprising a second plurality of programming instructions stored in a memory of, and operable on a processor of, a network-connected computing device, wherein the second plurality of programming instructions, when operating on the processor, cause the computing device to:

retrieve traffic data from the Internet; and

add the traffic data to the data graph.

5. The system of claim 1 , further comprising a map data retriever comprising a third plurality of programming instructions stored in a memory of, and operable on a processor of, a network-connected computing device, wherein the third plurality of programming instructions, when operating on the processor, cause the computing device to:

retrieve map data from the Internet or from a database;

determine a route for pick up or delivery of an order; and

send the route information to the delivery driver mobile device.

6. The system of claim 1 , wherein the schedule is optimized based on optimization selected from the following list:

minimum time from pickup to delivery of each order;

average time from pickup to delivery of a group of orders;

shortest distance traveled by each driver;

average distance traveled by a group of drivers;

earliest pickup time of each order;

average pickup time of a group of orders;

earliest delivery time of each order;

average delivery time of a group of orders; and

maximization of number of deliveries made without another pickup.

7. The system of claim 1 , wherein the data graph is a weighted graph.

8. The system of claim 1 , wherein the data graph is a directed graph.

9. A method for automated delivery driver routing and order preparation timing, comprising the steps of:

receiving availability information at an optimization engine comprising software operating on a network-connected computing device from one or more mobile devices each associated with a delivery driver, the availability information comprising a driver location, a vehicle type, a vehicle capacity, and routing information for orders currently in the vehicle for delivery, the routing information comprising one or more delivery locations and delivery times;

receiving order information at the optimization engine from one or more business enterprise computing devices for one or more orders, the order information for each order comprising an order identifier, a business enterprise location, a predicted order preparation time for each order, and a time that the order was placed;

creating a data graph using the optimization engine from the availability information and the order information, the data graph comprising vertices and edges, wherein the vertices represent data points, and the edges represent relationships between the data points;

analyzing the data graph using the optimization engine to create a schedule for order preparation, pickup, and delivery of each order;

sending a pickup request using the optimization engine to one or more of the delivery driver mobile devices for each order, the pickup request comprising the order identifier and a time for pickup; and

sending a preparation start time using the optimization engine to the business enterprise computing device, the preparation start time being calculated such that the order is ready at or before the time for pickup.

10. The method of claim 9 , wherein the availability information further comprises hours of availability of each driver.

11. The method of claim 9 , wherein the availability information further comprises one or more areas of operation of each driver.

12. The method of claim 9 , further comprising the steps of:

retrieving traffic data from the Internet; and

adding the traffic data to the data graph.

13. The method of claim 9 , further comprising the steps of:

retrieving map data from the Internet or from a database;

determining a route for pick up or delivery of an order; and

sending the route information to the delivery driver mobile device.

14. The method of claim 9 , wherein the schedule is optimized based on optimization selected from the following list:

minimum time from pickup to delivery of each order;

average time from pickup to delivery of a group of orders;

shortest distance traveled by each driver;

average distance traveled by a group of drivers;

earliest pickup time of each order;

average pickup time of a group of orders;

earliest delivery time of each order;

average delivery time of a group of orders; and

maximization of number of deliveries made without another pickup.

15. The method of claim 9 , wherein the data graph is a weighted graph.

16. The method of claim 9 , wherein the data graph is a directed graph.