Display space optimization

Patent metadata

Field	Value
Publication number	US-2016335586-A1
Application number	US-201514709702-A
Country	US
Kind code	A1
Filing date	May 12, 2015
Priority date	May 12, 2015
Publication date	Nov 17, 2016
Grant date	—

Abstract

Systems, methods, and other embodiments associated with assortment and display space optimization are described. In one embodiment, a method creates an optimal planogram. The example method includes receiving data describing i) a set of items described by item dimensions, ii) display space dimensions; iii) business rules, and iv) a key performance indicator. A set of possible shelf positions is identified for each item. An expected sales volume is calculated for each item and shelf position pair based, at least in part, on a selected demand model. The method includes providing i) the expected sales volume for the item and shelf position pairs, ii) a set of constraints that embody the business rules, and iii) an objective function to an optimization problem solver that computes a solution. Based on the solution, a planogram is output that specifies the assortment of items and respective optimal shelf positions of the items.

First claim

What is claimed is:

1 . A non-transitory computer storage medium storing computer-executable instructions that when executed by a computer cause the computer to construct a planogram, the instructions comprising:
instructions for receiving data describing i) a set of items selected from a corpus of items, where each item is described by item dimensions, ii) a display space; iii) business rules that constrain the selection and positioning of items in the display space, and iv) a key performance indicator; instructions for identifying a set of available shelf positions in the display space for each item in the set based, at least in part, on the item dimensions; instructions for calculating an expected sales volume for each item and available shelf position pair based, at least in part, on a selected demand model, instructions for providing i) the expected sales volume for the item and available shelf position pairs, ii) a set of constraints that embody the business rules, and iii) an objective function that expresses the key performance indicator as a function of the expected sales volumes to an optimization problem solver that, constrained by the set of constraints, computes a solution that specifies an assortment of the items selected from the set of items and, for each item in the assortment, an optimal shelf position, such that the key performance indicator is maximized; and instructions for outputting a planogram that specifies the assortment of items and respective optimal shelf positions of the items.

2 . The non-transitory computer storage medium of claim 1 , where the selected demand model predicts the expected sales volume for each item and shelf position pair based on i) a quantity of item facings produced by positioning the item in the shelf position and ii) a demand transference from items in the corpus that are not included in the set of items.

3 . The non-transitory computer storage medium of claim 1 , where the objective function includes a first component that characterizes demand transference from items in the set of items not selected for the assortment to items selected for the assortment and a second component that characterizes the self contribution to demand for items in the set.

4 . The non-transitory computer storage medium of claim 1 , where the business rules include a selected blocking strategy that defines whether related items are positioned in a horizontal blocks or vertical blocks within the display space.

5 . The non-transitory computer storage medium of claim 1 , where the instructions further comprise:
instructions for determining that the display space comprises a pegboard having pegholes evenly arranged according to a horizontal peg spacing and a vertical peg spacing; instructions for calculating the item dimensions for each item by, for each item:
rounding an actual item width up to a next integer multiple of horizontal peg spacing;
rounding an actual item height up to a next integer multiple of vertical peg spacing; and
instructions for determining shelf positions that correspond to blocks of pegholes by dividing the pegboard into a plurality of virtual shelves having respective dimensions determined based on a relationship between average item dimensions and dimensions of the pegboard; and where the instructions for calculating an expected sales volume for each item and available shelf position pair based on a selected demand model include instructions for calculating an expected sales volume for each item and virtual shelf pair.

6 . The non-transitory computer storage medium of claim 1 , where the instructions further comprise:
instructions for, prior to identifying a set of available shelf positions in the display space for each item in the set:
determining if the set of items violates any of the business rules; and
when the set of items violates a business rule, reporting infeasibility without identifying a set of available shelf positions.

7 . The non-transitory computer storage medium of claim 1 , where the instructions further comprise:
instructions for calculating an expected service level for each item and available shelf position pair based on the selected demand model, and instructions for providing the expected service level for the item and shelf position pairs in addition to the expected sales volume for each item and shelf position pair to the optimization problem solver such that the optimization problem solver considers the expected service levels in a first solving operation; and instructions for providing only the expected sales volume for the item and shelf position pairs to the optimization problem solver when the optimization problem solver fails to find a solution in the first solving operation, such that the optimization problem solver does not consider the expected service levels in a second solving operation; and instructions for reporting infeasibility when the optimization problem solver fails to find a solution in either the first solving operation or the second solving operation.

8 . A computing system comprising:
input logic configured to:
receive data describing i) a set of items selected from a corpus of items, where each item is described by item dimensions, ii) a display space; iii) business rules that constrain the selection and positioning of items in the display space, and iv) a key performance indicator;
identify a set of available shelf positions in the display space for each item in the set based, at least in part, on the item dimensions;
calculate an expected sales volume for each item and available shelf position pair based, at least in part, on a selected demand model;
constraint logic configured to generate a set of constraints that embody the business rules; and function logic configured to generate an objective function that expresses the key performance indicator as a function of the expected sales volumes; formulation logic configured to:
provide, to an optimization problem solver, provide i) the expected sales volume for the item and available shelf position pairs, the set of constraints, and the objective function, such that the optimization problem solver, constrained by the set of constraints, computes a solution that specifies an assortment of the items selected from the set of items and, for each item in the assortment, an optimal shelf position, such that the key performance indicator is maximized; and
output a planogram that specifies the assortment of items and respective optimal shelf positions of the items.

9 . The computing system of claim 8 , where the selected demand model predicts the expected sales volume for each item and shelf position pair based on i) a quantity of item facings produced by positioning the item in the shelf position and ii) a demand transference from items in the corpus that are not included in the set of items.

10 . The computing system of claim 8 , where the objective function includes a first component that characterizes demand transference from items in the set of items not selected for the assortment to items selected for the assortment and a second component that characterizes the self contribution to demand for items in the set.

11 . The computing system of claim 8 , where the business rules include a selected blocking strategy that defines whether related items are positioned in a horizontal blocks or vertical blocks within the display space.

12 . The computing system of claim 8 , where the input logic is further configured to determine that the display space comprises a pegboard having pegholes evenly arranged according to a horizontal peg spacing and a vertical peg spacing, the computing system

Assignees

• Oracle Int Corp

Inventors

• Panchamgam Kiran V

Classifications

• G06Q10/087 Primary

  Inventory or stock management, e.g. order filling, procurement or balancing against orders · CPC title

• A47F5/0823

  Article supports for peg-boards · CPC title

• A47F5/0043

  Show shelves (shelves in general A47B96/02; brackets or similar shelf-supporting means A47B96/06; advertising or price indication G09F) · CPC title

• G06Q10/08724 Primary

  by shelf level inventory management, e.g. planograms · CPC title