IP Library Granted Patent US 10,909,495
Granted Patent B2
US 10,909,495 · App. 15/642,970 · Granted Feb 2, 2021

Systems and methods for implementing incentive-based demand distribution techniques using queue time estimates

Inventors: Pratosh Deepak Rajkhowa (Bangalore, IN); Vidyanand Krishnan (Sunnyvale, CA)
Assignee: WAL-MART STORES, INC.
G06Q10/0836G06F17/18G06Q10/1095
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Quick Facts
Patent No.
US 10,909,495
App. No.
15/642,970
Granted
Feb 2, 2021
Kind
B2
Abstract

Systems and methods are described which utilize improved scheduling techniques. An electronic scheduling platform enables customers to view and select pick-up options for scheduling orders to be retrieved at a location. Each pick-up option is associated with a price and a queue time. An average service time and an average inter-arrival time is determined for the location. A queuing procedure is executed which calculates queue times and prices for the pick-up options based, at least in part, on the average service time and the average inter-arrival time. The queuing procedure dynamically updates in real-time the calculated queue times and prices for the pick-up options. Instructions are generated for providing an interface that displays at least a portion of the pick-up options with the updated queue times and prices.

Claims (125)

1. A system comprising:

one or more processors; and

one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform:

providing an electronic scheduling platform that enables customers to view and select pick-up options for scheduling orders to be retrieved at a location, each pick-up option being associated with a respective price and a respective queue time for scheduling a respective order of the orders within a respective time period associated with the pick-up option;

determining an average service time indicating an average amount of time associated with processing an order at the location and an average inter-arrival time indicating an average arrival rate of the customers at the location, wherein the average service time and the average inter-arrival time are determined by (a) monitoring operations associated with service times and inter-arrival times at the location and (b) dynamically updating the average service time and the average inter-arrival time;

in response to a customer of the customers accessing the electronic scheduling platform, executing a queuing procedure that is used to calculate queue times and that is used to determine prices for the pick-up options based, at least in part, by the average service time, utilization that represents the average service time and the average inter-arrival time, and a sum of a coefficient of variation of inter-arrival times and a coefficient of variation of service times;

in response to the customers scheduling the orders, applying the queuing procedure to dynamically update the queue times and the prices that are calculated for the pick-up options; and

generating instructions for providing an interface that displays at least a portion of the pick-up options with the queue times and the prices that are updated.

2. The system of claim 1 , wherein the queuing procedure is further used to dynamically update the queue times and the prices that are calculated for the pick-up options such that the prices associated with the pick-up options increase as the queue times associated with the pick-up options increase.

3. The system of claim 1 , wherein the queuing procedure is used to further calculate the queue times using a formula:

Queue

Time

=

Average

Service

Time

*

(

Utilization

1

-

Utilization

)

*

(

Cv

a

2

+

CVp

2

)

/

2

where,

utilization represents the average service time/the average inter-arrival time;

the average service time represents an average amount of time it takes to service the customers at the location;

the average inter-arrival time represents an average amount of time between a respective arrival of each of the customers at the location;

CVa 2 represents the coefficient of variation of inter-arrival times; and

CVp 2 represents the coefficient of variation of service times.

4. The system of claim 1 , wherein the queuing procedure is further used to calculate the respective price for a pick-up option based, at least in part, on (i) a number of customers that have previously scheduled orders for the pick-up option and (ii) the respective queue time calculated for the pick-up option.

5. The system of claim 1 , wherein the computing instructions are further configured to run on the one or more processors and perform:

for each of the pick-up options, determining a maximum slot size indicating a maximum number of customers that are able to request respective orders within the respective time period associated with the pick-up option; and

utilizing the maximum slot size to place limits on how many of the respective orders can be scheduled within each of the pick-up options.

6. The system of claim 1 , wherein the average service time and the average inter-arrival time are further determined by analyzing input data from monitoring equipment comprising a camera and a sensor located at the location.

7. The system of claim 1 , wherein the average service time and the average inter-arrival time are further determined by retrieving pre-determined values which are stored on the one or more non-transitory computer-readable media.

8. The system of claim 1 , wherein the queuing procedure is used to further calculate the prices using a formula:

Price=(NumOfPeople*Queue Time*WeightMul)+WeightCon

where,

NumOfPeople represents a number of customers who have previously scheduled orders in a time period associated with a particular pick-up option;

Queue Time represents an estimated queue time that the customers will wait at the location when picking up the orders;

WeightMul represents a weighting value multiplier that is associated with a particular queue time; and

WeightCon represents a weighting value constant that is associated with the particular queue time.

9. The system of claim 1 , wherein the electronic scheduling platform communicates with a plurality of user computers operated by the customers over a network that includes one or more of:

an Internet, a local area network, a wide area network, an intranet, or an extranet.

10. The system of claim 1 , wherein the location is selected from a group consisting of:

a retail location and a pick-up locker.

11. A method comprising:

providing, with one or more processors, an electronic scheduling platform that enables customers to view and select pick-up options for scheduling orders to be retrieved at a location, each pick-up option being associated with a respective price and a respective queue time for scheduling a respective order of the orders within a respective time period associated with the pick-up option;

determining an average service time indicating an average amount of time associated with processing an order at the location and an average inter-arrival time indicating an average arrival rate of the customers at the location, wherein the average service time and the average inter-arrival time are determined by (a) monitoring operations associated with service times and inter-arrival times at the location and (b) dynamically updating the average service time and the average inter-arrival time;

in response to a customer of the customers accessing the electronic scheduling platform, executing, with the one or more processors, a queuing procedure that is used to calculate queue times and that is used to determine prices for the pick-up options based, at least in part, by the average service time, utilization that represents the average service time and the average inter-arrival time, and a sum of a coefficient of variation of inter-arrival times and a coefficient of variation of service times;

in response to the customers scheduling the orders, applying the queuing procedure to dynamically update the queue times and the prices that are calculated for the pick-up options; and

generating, with the one or more processors, instructions for providing an interface that displays at least a portion of the pick-up options with the queue times and the prices that are updated.

12. The method of claim 11 , wherein the queuing procedure is further used to dynamically update the queue times and the prices that are calculated for the pick-up options such that the prices associated with the pick-up options increase as the queue times associated with the pick-up options increase.

13. The method of claim 11 , wherein the queuing procedure is further used to calculate the queue times using a formula:

Queue

Time

=

Average

Service

Time

*

(

Utilization

1

-

Utilization

)

*

(

CVa

2

+

CVp

2

)

/

2

where,

utilization represents the average service time/the average inter-arrival time;

the average service time represents an average amount of time it takes to service the customers at the location;

the average inter-arrival time represents an average amount of time between a respective arrival of each of the customers at the location;

CVa 2 represents the coefficient of variation of inter-arrival times; and

CVp 2 represents the coefficient of variation of service times.

14. The method of claim 11 , wherein the queuing procedure is further used to calculate the respective price for a pick-up option based, at least in part, on (i) a number of customers that have previously scheduled orders for the pick-up option and (ii) the respective queue time calculated for the pick-up option.

15. The method of claim 11 , wherein the method further comprises:

for each of the pick-up options, determining a maximum slot size indicating a maximum number of customers that are able to request respective orders within the respective time period associated with the pick-up option; and

utilizing the maximum slot size to place limits on how many of the respective orders can be scheduled within each of the pick-up options.

16. The method of claim 11 , wherein the average service time and the average inter-arrival time are further determined by analyzing input data from monitoring equipment comprising a camera and a sensor located at the location.

17. The method of claim 11 , wherein the average service time and the average inter-arrival time are further determined by retrieving pre-determined values which are stored on one or more non-transitory computer-readable media.

18. The method of claim 11 , wherein the queuing procedure is further used to calculate the prices using a formula:

Price=(NumOfPeople*Queue Time*WeightMul)+WeightCon

where,

NumOfPeople represents a number of customers who have previously scheduled orders in a time period associated with a particular pick-up option;

Queue Time represents an estimated queue time that the customers will wait at the location when picking up the orders;

WeightMul represents a weighting value multiplier that is associated with a particular queue time; and

WeightCon represents a weighting value constant that is associated with the particular queue time.

19. The method of claim 11 , wherein the electronic scheduling platform communicates with a plurality of user computers operated by the customers over a network that includes one or more of:

an Internet, a local area network, a wide area network, an intranet, or an extranet.

20. The method of claim 11 , wherein the location is selected from a group consisting of:

a retail location and a pick-up locker.

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 17, 2022
From: WAL-MART STORES, INC.
To: WALMART APOLLO, LLC
Reel/Frame 059036/0629 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 31, 2020
From: WM GLOBAL TECHNOLOGY SERVICES INDIA PRIVATE LIMITED
To: WAL-MART STORES, INC.
Reel/Frame 054787/0768 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 23, 2018
From: RAJKHOWA, PRATOSH DEEPAK
To: WM GLOBAL TECHNOLOGY SERVICES INDIA PRIVATE LIMITED
Reel/Frame 046430/0855 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 6, 2017
From: RAJKHOWA, PRATOSH DEEPAK; KRISHNAN, VIDYANAND
To: WAL-MART STORES, INC.
Reel/Frame 042926/0747 →
Continuity (1)
Related Publication 20190012638A1 · Jan 10, 2019