Systems and methods for dual optimization of pick walk and tote fill rates for order picking

Patent metadata

Field	Value
Publication number	US-11074547-B2
Application number	US-201816040910-A
Country	US
Kind code	B2
Filing date	Jul 20, 2018
Priority date	Apr 20, 2018
Publication date	Jul 27, 2021
Grant date	Jul 27, 2021

Abstract

Methods and systems and computer-readable media are provided for dual optimization of pick walk and tote fill rates in order picking. Embodiments provide improved order picking speed and quality by optimizing pick routing with consideration of both proximity constraints and tote value constraints. Tote value constraints can include constraints on carrying capacity, volume, size in a particular dimension, or weight capacity.

First claim

The invention claimed is:

1. A system for the dual optimization of pick walks and tote fill rates for order picking, comprising:
a plurality of totes, each tote having a physical capacity;
a plurality of carts wherein each cart is configured to support a specified number of the plurality of totes and is operated by one of a plurality of pickers;
a plurality of mobile devices respectively associated with the plurality of pickers;
a server communicatively coupled to a database holding information regarding each item in a facility, the server configured to execute an item list optimization module that when executed:
receives a plurality of orders, each order including a list of one or more items,
determines an order batch to be picked for each of the plurality of pickers, each batch including items associated with one or more of the plurality of orders, the determining including:
assigning items from a first order as a first batch to a first picker;
performing an optimization determination based on proximity constraints and tote value constraints for each additional order in the plurality of orders that determines whether items from the additional order are added to an existing batch or are assigned a new batch, the tote value constraints based on the weight and size attributes of the items and including a maximum weight constraint of each tote, and
assigning, based on a result of the optimization determination, items in the plurality of orders to a plurality of batches, wherein the assigning the items in the plurality of orders to the plurality of batches comprises:
dividing the items in each assigned batch into two halves;
summing the size attributes for items in the first half for each assigned batch;
summing the size attributes for items in the second half for each assigned batch;
in response to the sum of size attributes for items in the second half being greater than the sum of size attributes for items in the first half for the assigned batch, reversing a sequence of items in the assigned batch; and

transmits the plurality of assigned batches to the plurality of pickers via the plurality of mobile devices.

2. The system of claim 1 , wherein the information for each item in the database includes weight and size attributes and a location within the facility, the optimization module further configured to:
determine proximity constraints based on the location information.

3. The system of claim 2 , wherein the size attributes correspond to at least one of volume, length, height, or width.

4. The system of claim 1 , wherein the items are grocery items.

5. The system of claim 1 , wherein assigning items in the plurality of orders to the plurality of batches includes ordering items in each batch that reside on a same shelving unit from top to bottom and from left to right.

6. A method for dual optimization of pick walks and tote fill rates for order picking, comprising:
receiving a plurality of orders, each order including a list of one or more items;
determining an order batch to be picked for each of a plurality of pickers that operate a plurality of carts, each cart configured to support a specified number of a plurality of totes, each tote having a physical capacity, wherein determining includes:
assigning items from a first order as a first batch to a first picker,
performing an optimization determination based on proximity constraints and tote
value constraints for each additional order in the plurality of orders that determines whether items from the additional order are added to an existing batch or are assigned to a new batch, the tote value constraints based on the weight and size attributes of the items and including a maximum weight constraint of each tote, and
assigning, based on the result of the optimization determination, items in the plurality of orders to a plurality of batches, wherein the assigning the items in the plurality of orders to the plurality of batches comprises:
dividing the items in each assigned batch into two halves;
summing the size attributes for items in the first half for each assigned batch;
summing the size attributes for items in the second half for each assigned batch;
in response to the sum of size attributes for items in the second half being greater than the sum of size attributes for items in the first half for the assigned batch, reversing a sequence of items in the assigned batch; and

transmitting the plurality of assigned batches to the plurality of pickers via a plurality of mobile devices respectively associated with the plurality of pickers.

7. The method of claim 6 , further comprising:
accessing a database holding weight and size attributes for each item in a facility and a location for each item within the facility, and
wherein performing the optimization determination includes:
determining proximity constraints based on the location information.

8. The method of claim 7 , wherein the size attributes correspond to at least one of volume, length, height, or width.

9. The method of claim 6 , wherein the items are grocery items.

10. The method of claim 6 , wherein assigning items in the plurality of orders to the plurality of batches includes ordering items in each batch that reside on a same shelving unit from top to bottom and from left to right.

11. A non-transitory computer readable medium for dual optimization of pick walks and tote fill rates for order picking, the medium having stored thereon instructions that when executed in a computing system, cause the computing system to perform operations comprising:
receiving a plurality of orders, each order including a list of one or more items;
determining an order batch to be picked for each of a plurality of pickers that operate a plurality of carts, each cart configured to support a specified number of a plurality of totes, each tote having a physical capacity, wherein determining includes:
assigning items from a first order as a first batch to a first picker, performing an optimization determination based on proximity constraints and tote value constraints for each additional order in the plurality of orders that determines whether items from the additional order are added to an existing batch or are assigned to a new batch, the tote value constraints based on the weight and size attributes of the items and including a maximum weight constraint of each tote, and,
assigning, based on the result of the optimization determination, items in the plurality of orders to a plurality of batches, wherein the assigning the items in the plurality of orders to the plurality of batches comprises:
dividing the items in each assigned batch into two halves;
summing the size attributes for items in the first half for each assigned batch;
summing the size attributes for items in the second half for each assigned batch;
in response to the sum of size attributes for items in the second half being greater than the sum of size attributes for items in the first half for the assigned batch, reversing a sequence of items in the assigned batch; and

transmitting the plurality of assigned batches to the plurality of pickers via a plurality of mobile devices respectively associated with the plurality of pickers.

12. The computer readable medium of claim 11 , wherein the instructions further cause the computer to perform operations comprising:
accessing a database holding weight and size attributes for each item in a facility and a location for each item within the facility, and
wherein performing the optimization determination includes:
determining proximity constraints based on the location information.

13. The computer

Assignees

• Walmart Apollo Llc

Inventors

• Rajkhowa Pratosh
• Shendre Ameya Ajay
• Gupta Shekhar
• Kumar Pavan

Classifications

• G06Q10/087 Primary

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

• G06Q10/04 Primary

  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) · CPC title

• G06Q10/08

  Logistics, e.g. warehousing, loading or distribution; Inventory or stock management · CPC title