# US 8,788,315 B2 · Systems and methods for determining pack allocations

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- Number: US 8,788,315 B2
- Document ID: US8788315B2
- Status: Granted
- Kind: B2
- Application number: 12/987,486
- Filed: 2011-01-10
- Published: 2012-07-12
- Granted: 2014-07-22
- Earliest claimed: 2011-01-10
- Assignees: SAS Institute Inc.
- Applicants: Teresa DePaola McMains; Thomas Burkhardt; Robert William Pratt
- Inventors: Teresa DePaola McMains; Thomas Burkhardt; Robert William Pratt
- Web page: https://patentgrep.com/patent/US8788315B2

## CPC

- G06Q 10/04: Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202)
- G06Q 10/06315: {Needs-based resource requirements planning or analysis}
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR

## Abstract

Systems and methods are provided for determining a plurality of pack configurations to make available for distribution to a plurality of stores, wherein a pack configuration contains a particular number of units of each of a plurality of variations of a product. An allowable pack size constraint, a maximum pack configuration constraint, mismatch cost data, and product demand data for the plurality of stores are received. A first pack and a second pack for the store are determined, wherein the first pack contains a particular number of each of the variations of the product, wherein the first pack meets the allowable pack size constraint and minimizes mismatch costs for the store. Stores are clustered based on similarity of their demand data until the total pack configuration amount across all clusters meets the maximum pack configuration constraint.

## Claims

### Claim 1

A computer-implemented method comprising:
receiving demand profile information corresponding to each store in a group of stores, wherein the demand profile information is received at a computing apparatus and indicates anticipated demand for each of multiple varieties of a product at each store;
receiving mismatch cost data for each store in the group, wherein the mismatch cost data includes:
a set of overdelivery costs for each store, each set of overdelivery costs including an overdelivery cost for each variety of the product, wherein each overdelivery cost is a marginal cost incurred when more than a demanded amount of the respective variety is shipped to the respective store; and
a set of underdelivery costs for each store, each set of underdelivery costs including an underdelivery cost for each variety of the product, wherein each underdelivery cost is a marginal cost incurred when less than a demanded amount of the respective variety is shipped to the respective store;
receiving one or more constraints;
with respect to each store in the group, defining an initial pack configuration, wherein defining includes using the demand profile information, the mismatch cost data, and the one or more constraints, and, wherein the pack configuration facilitates lowest total mismatch costs for a corresponding store;
planning shipments of the product to the stores, wherein planning includes selecting at least one, but less than all of the initial pack configurations, wherein selecting the at least one of the initial pack configurations includes using a pack elimination process that is executed on a computing device and includes:
accessing information representing a constraint that imposes a maximum number of distinct pack configurations with respect to each of the shipments;
forming multiple initial clusters of the stores by grouping each of the stores with at least one other of the stores based on similarities between characteristics of the stores;
with respect to each of the initial clusters of the stores:
selecting a representative pack configuration from amongst the initial pack configurations defined with respect to the stores of the initial cluster;
grouping at least two of the initial clusters based on similarities between the representative pack configurations selected with respect to the initial clusters;
eliminating at least one of the representative pack configurations selected with respect to the grouped initial clusters; and
determining that the representative pack configurations not eliminated by the pack elimination process amount to not more than the maximum number of distinct pack configurations; and
specifying that the planned shipments be made using the representative pack configurations not eliminated by the pack elimination process.

### Claim 2 (depends on 1)

The method of claim 1, wherein the characteristics of the stores include store associations with distribution centers.

### Claim 3 (depends on 2)

The method of claim 2, wherein grouping each of the stores based on similarities between characteristics includes grouping a first one of the stores with a second one of the stores in response to determining that both the first one of the stores and the second one of the stores are served by a same distribution center.

### Claim 4 (depends on 1)

The method of claim 1, wherein, with respect to each of the initial clusters of the stores:
mismatch cost data with respect to the stores of the initial cluster is used in selecting the representative pack configuration from amongst the initial pack configurations defined with respect to the stores of the initial cluster.

### Claim 5 (depends on 1)

The method of claim 1, wherein each of the initial pack configurations is defined in accordance with a constraint that imposes a maximum number of items that can be present in a pack configuration.

### Claim 6 (depends on 1)

The method of claim 1, wherein further, the following operations are repeatedly performed using an iterative process, prior to determining that the representative pack configurations not eliminated by the pack elimination process amount to not more than the maximum number:
grouping at least two of the initial clusters based on similarities between the representative pack configurations selected with respect to the initial clusters; and
eliminating at least one of the representative pack configurations selected with respect to the grouped initial clusters.

### Claim 7 (depends on 6)

The method of claim 6, wherein the product is clothing and the multiple varieties of the product include multiple sizes of the clothing.

### Claim 8

A computer-implemented system, comprising:
one or more data processors; and
one or more non transitory computer-readable storage media containing instructions operable to cause the one or more processors to perform operations including:
receiving demand profile information corresponding to each store in a group of stores, wherein the demand profile information indicates anticipated demand for each of multiple varieties of a product at each store;
receiving mismatch cost data for each store in the group, wherein the mismatch cost data includes:
a set of overdelivery costs for each store, each set of overdelivery costs including an overdelivery cost for each variety of the product, wherein each overdelivery cost is a marginal cost incurred when more than a demanded amount of the respective variety is shipped to the respective store; and
a set of underdelivery costs for each store, each set of underdelivery costs including an underdelivery cost for each variety of the product, wherein each underdelivery cost is a marginal cost incurred when less than a demanded amount of the respective variety is shipped to the respective store;
receiving one or more constraints;
with respect to each store in the group, defining an initial pack configuration, wherein defining includes using the demand profile information, the mismatch cost data, and the one or more constraints, and, wherein the pack configuration facilitates lowest total mismatch costs for a corresponding store;
planning shipments of the product to the stores, wherein planning includes selecting at least one, but less than all of the initial pack configurations, wherein selecting the at least one of the initial pack configurations includes using a pack elimination process that includes:
accessing information representing a constraint that imposes a maximum number of distinct pack configurations with respect to each of the shipments;
forming multiple initial clusters of the stores by grouping each of the stores with at least one other of the stores based on similarities between characteristics of the stores;
with respect to each of the initial clusters of the stores:
selecting a representative pack configuration from amongst the initial pack configurations defined with respect to the stores of the initial cluster;
grouping at least two of the initial clusters based on similarities between the representative pack configurations selected with respect to the initial clusters;
eliminating at least one of the representative pack configurations selected with respect to the grouped initial clusters; and
determining that the representative pack configurations not eliminated by the pack elimination process amount to not more than the maximum number of distinct pack configurations; and
specifying that the planned shipments be made using the representative packs not eliminated by the pack elimination process.

### Claim 9 (depends on 8)

The system of claim 8, wherein the characteristics of the stores include store associations with distribution centers.

### Claim 10 (depends on 9)

The system of claim 9, wherein grouping each of the stores based on similarities between characteristics includes grouping a first one of the stores with a second one of the stores in response to determining that both the first one of the stores and the second one of the stores are served by a same distribution center.

### Claim 11 (depends on 8)

The system of claim 8, wherein, with respect to each of the initial clusters of the stores:
mismatch cost data with respect to the stores of the initial cluster is used in selecting the representative pack configuration from amongst the initial pack configurations defined with respect to the stores of the initial cluster.

### Claim 12 (depends on 8)

The system of claim 8, wherein each of the initial pack configurations is defined in accordance with a constraint that imposes a maximum number of items that can be present in a pack configuration.

### Claim 13 (depends on 8)

The system of claim 8, wherein further, the following operations are repeatedly performed using an iterative process, prior to determining that the representative pack configurations not eliminated by the pack elimination process amount to not more than the maximum number:
grouping at least two of the initial clusters based on similarities between the representative pack configurations selected with respect to the initial clusters; and
eliminating at least one of the representative pack configurations selected with respect to the grouped initial clusters.

### Claim 14 (depends on 13)

The system of claim 13, wherein the product is clothing and the multiple varieties of the product include multiple sizes of the clothing.

### Claim 15

A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, the computer-program product including instructions operable to cause a data processing apparatus to perform operations including:
receiving demand profile information corresponding to each store in a group of stores, wherein the demand profile information indicates anticipated demand for each of multiple varieties of a product at each store;
receiving mismatch cost data for each store in the group, wherein the mismatch cost data includes:
a set of overdelivery costs for each store, each set of overdelivery costs including an overdelivery cost for each variety of the product, wherein each overdelivery cost is a marginal cost incurred when more than a demanded amount of the respective variety is shipped to the respective store; and
a set of underdelivery costs for each store, each set of underdelivery costs including an underdelivery cost for each variety of the product, wherein each underdelivery cost is a marginal cost incurred when less than a demanded amount of the respective variety is shipped to the respective store;
receiving one or more constraints;
with respect to each store in the group, defining an initial pack configuration, wherein defining includes using the demand profile information, the mismatch cost data, and the one or more constraints, and, wherein the pack configuration facilitates lowest total mismatch costs for a corresponding store;
planning shipments of the product to the stores, wherein planning includes selecting at least one, but less than all of the initial pack configurations, wherein selecting the at least one of the initial pack configurations includes using a pack elimination process that includes:
accessing information representing a constraint that imposes a maximum number of distinct pack configurations with respect to each of the shipments;
forming multiple initial clusters of the stores by grouping each of the stores with at least one other of the stores based on similarities between characteristics of the stores;
with respect to each of the initial clusters of the stores:
selecting a representative pack configuration from amongst the initial pack configurations defined with respect to the stores of the initial cluster;
grouping at least two of the initial clusters based on similarities between the representative pack configurations selected with respect to the initial clusters;
eliminating at least one of the representative pack configurations selected with respect to the grouped initial clusters; and
determining that the representative pack configurations not eliminated by the pack elimination process amount to not more than the maximum number of distinct pack configurations; and
specifying that the planned shipments be made using the representative pack configurations not eliminated by the pack elimination process.

### Claim 16 (depends on 15)

The computer-program product of claim 15, wherein the characteristics of the stores include store associations with distribution centers.

### Claim 17 (depends on 16)

The computer-program product of claim 16, wherein grouping each of the stores based on similarities between characteristics includes grouping a first one of the stores with a second one of the stores in response to determining that both the first one of the stores and the second one of the stores are served by a same distribution center.

### Claim 18 (depends on 15)

The computer-program product of claim 15, wherein, with respect to each of the initial clusters of the stores:
mismatch cost data with respect to the stores of the initial cluster is used in selecting the representative pack configuration from amongst the initial pack configurations defined with respect to the stores of the initial cluster.

### Claim 19 (depends on 15)

The computer-program product of claim 15, wherein each of the initial pack configurations is defined in accordance with a constraint that imposes a maximum number of items that can be present in a pack configuration.

### Claim 20 (depends on 15)

The computer-program product of claim 15, wherein further, the following operations are repeatedly performed using an iterative process, prior to determining that the representative pack configurations not eliminated by the pack elimination process amount to not more than the maximum number:
grouping at least two of the initial clusters based on similarities between the representative pack configurations selected with respect to the initial clusters; and
eliminating at least one of the representative pack configurations selected with respect to the grouped initial clusters.

### Claim 21 (depends on 15)

The computer-program product of claim 15, wherein the product is clothing and the multiple varieties of the product include multiple sizes of the clothing.