US 12,086,867 B2
Methods and apparatus for generating planograms
Yijia Yang, Pasadena, CA (US); and Mohit Batham, Karnataka (IN)
Assigned to Walmart Apollo, LLC, Bentonville, AR (US)
Filed by Walmart Apollo, LLC, Bentonville, AR (US)
Filed on Jan. 31, 2022, as Appl. No. 17/589,752.
Prior Publication US 2023/0245216 A1, Aug. 3, 2023
Int. Cl. G06Q 30/0601 (2023.01); G06Q 10/087 (2023.01)
CPC G06Q 30/0639 (2013.01) [G06Q 10/087 (2013.01); G06Q 30/0603 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system comprising:
a memory resource storing instructions; and
one or more processors coupled to the memory resource, the one or more processors configured to execute the instructions to:
provide a service application to a computing device which may be utilized to generate, by the service application, a user-interface (UI) that includes at least one or more interactive features that enable the user to implement a set of input data which includes at least one or more of constraint data or user defined parameters, wherein the input data is transmitted to the one or more processors;
obtain modular data of a shelf-peg modular, item data of a group of items associated with an item type of the shelf-peg modular, and draw strategy data, wherein the draw strategy includes a sequencing elasticity parameter, a blockiness parameter, a blockiness elasticity parameter, a striping parameter, and an item placement flexibility parameter;
extract, from the modular data, data characterizing a shelf portion of the shelf-peg modular and data characterizing a peg portion of the shelf-peg modular;
based on the data characterizing the shelf portion, the item data, and the draw strategy data, implement a first set of modular placement optimization operations, by a shelf optimization engine, that generate a first modular dataset of the shelf portion of the shelf-peg modular;
based on data characterizing the peg portion, the modular data of the shelf portion, the item data, the first modular dataset, and the draw strategy data, determine dimensional information of the peg portion;
based on the data characterizing the peg portion of the shelf-peg modular, the dimensional information of the peg portion, the item data, the first modular dataset, and the draw strategy data, implement a second set of modular placement optimization operations that generate a second modular dataset of the peg portion of the shelf-peg modular;
determine, by the shelf optimization engine, a score of the first and the second modular dataset based on a sum average of a ranking of each item of the item data in the corresponding first and second modular dataset;
in response to determining the score of the first and the second modular dataset, generate a planogram data structure based on a highest score of the first and second modular dataset; and
generate, by the service application provided to the computing device, a graphical representation of the planogram data structure.