Systems And Methods For Generating Planograms In The Presence Of Multiple Objectives

• US 20110035257A1
• Filed: 08/06/2009
• Published: 02/10/2011
• Est. Priority Date: 08/06/2009
• Status: Abandoned Application

• Current Assignee: SAS Institute Incorporated
• Original Assignee: SAS Institute Incorporated
• Inventors: Kong, Seung Hyun, Solanki, Rajendra Singh, Hu, Jennie (Jing)
• Application Number:
  US12/537,023
• Publication Number:
  US 20110035257A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 10/043 Optimisation of two dimensional placement, e.g. cutting of clothes or wood
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Systems and methods for an item placement configuration optimization are provided. A system and method can include receiving a first selection including two or more first items corresponding to a first level in an item placement configuration. A first score is determined for the first selection by applying an algorithm to data corresponding to the first items. A second selection including two or more second items and corresponding to a second level in the item placement configuration is received. A second score for the second selection is determined by applying an algorithm to the first score and data corresponding to the second items.

Claims

1. A computer-implemented method, comprising:

executing instructions in a processor-implemented system for receiving a first selection corresponding to a first level in an item placement configuration, the first selection including two or more first items;

executing instructions in the processor-implemented system for determining a first score for the first selection, wherein scoring includes applying an algorithm to data corresponding to the first items;

executing instructions in the processor-implemented system for receiving a second selection corresponding to a second level in the item placement configuration, the second selection including two or more second items; and

executing instructions in the processor-implemented system for determining a second score for the second selection, wherein scoring includes applying an algorithm to the first score and data corresponding to the second items.

2. The method of claim 1, further comprising:

executing instructions in the processor-implemented system for determining if there is a saved score corresponding the first selection, and

executing instructions in the processor-implemented system for using the higher of the saved score or the first score to determine the second score.

3. The method of claim 2, further comprising:

executing instructions in the processor-implemented system for replacing the saved score with the first score, when the first score is higher.

4. The method of claim 1, further comprising:

executing instructions in the processor-implemented system for optimizing the item placement configuration according to one or more objectives including a facings objective, a shape objective, or a sequence objective.

5. A computer-implemented method for determining placements of products with respect to one or more shelves, comprising:

executing instructions in a processor-implemented system for receiving first product placement attribute data including at least one of;

product priority data, layer of shortfall, layer of excess data, or product facing data;

executing instructions in the processor-implemented system for creating product placement scores by solving a non-linear product placement mathematical formulation using the first product placement attribute data and one or more product placement objectives, the non-linear product placement mathematical formulation including at least one non-linear interrelationship that exists with respect to the product placement attribute data;

executing instructions in the processor-implemented system for creating product placement configurations with respect to the one or more shelves; and

executing instructions in the processor-implemented system for associating each of the product placement configurations with a product placement score to determine an optimal product placement configuration, the product placement configuration being optimal with respect to the one or more product placement objectives.

6. The computer-implemented method of claim 5, wherein a first product placement score corresponds to a product placement configuration on a first level.

7. The computer-implemented method of claim 6, further comprising:

executing instructions in the processor-implemented system for receiving second product placement attribute data including at least one of;

product priority data, layer of shortfall, layer of excess data, or product facing data, the second product placement attribute data corresponding to a product placement configuration on a second level, and

executing instructions in the processor-implemented system for determining a second product placement score for the second product placement attribute data by solving the non-linear product placement mathematical formulation using the first product placement score and the second product placement attribute data.

8. A system, comprising:

a processor;

a computer-readable storage medium containing instructions which when executed on the processor, cause the processor to perform operations including;

receiving a first selection corresponding to a first level in an item placement configuration, the first selection including two or more first items;

determining a first score for the first selection, wherein scoring includes applying an algorithm to data corresponding to the first items;

receiving a second selection corresponding to a second level in the item placement configuration, the second selection including two or more second items; and

determining a second score for the second selection, wherein scoring includes applying an algorithm to the first score and data corresponding to the second items.

9. The system of claim 8, further comprising:

determining if there is a saved score corresponding the first selection, and

using the higher of the saved score or the first score to determine the second score.

10. The system of claim 9, further comprising:

replacing the saved score with the first score, when the first score is higher.

11. The system of claim 8, further comprising:

optimizing the item placement configuration according to one or more objectives including a facings objective, a shape objective, or a sequence objective.

12. Computer-readable storage medium or mediums encoded with instructions that when executed, cause a computer to perform a method for determining placements of products with respect to one or more shelves, the method comprising:

receiving first product placement attribute data including at least one of;

product priority data, layer of shortfall, layer of excess data, or product facing data;

creating product placement scores by solving a non-linear product placement mathematical formulation using the first product placement attribute data and one or more product placement objectives, the non-linear product placement mathematical formulation including at least one non-linear interrelationship that exists with respect to the product placement attribute data;

creating product placement configurations with respect to the one or more shelves; and

associating each of the product placement configurations with a product placement score to determine an optimal product placement configuration, the product placement configuration being optimal with respect to the one or more product placement objectives.

13. The method of claim 12, wherein a first product placement score corresponds to a product placement configuration on a first level.

14. The method of claim 13, further comprising:

receiving second product placement attribute data including at least one of;

product priority data, layer of shortfall, layer of excess data, or product facing data, the second product placement attribute data corresponding to a product placement configuration on a second level, and

determining a second product placement score for the second product placement attribute data by solving the non-linear product placement mathematical formulation using the first product placement score and the second product placement attribute data.