Systems and Methods for Fulfilment Design & Optimization

Patent metadata

Field	Value
Publication number	US-2018330316-A1
Application number	US-201815977777-A
Country	US
Kind code	A1
Filing date	May 11, 2018
Priority date	May 11, 2017
Publication date	Nov 15, 2018
Grant date	—

Abstract

A system for fulfillment & optimization. The system includes an optimization engine that executes scenario simulations, wherein the scenario simulations generate pick information. The optimization engine selects a best scenario from at least two scenarios based on the scenario information. In response to the selection of the best scenario, the optimization engine configures a computing system to execute a zoning policy, a routing policy, and a base algorithm policy associated with the best scenario. The computing system executes the zoning policy, the routing policy, and the base algorithm policy to fulfill orders.

First claim

We claim:

1 . A system for reconfiguring a computing system to execute best policies, the system comprising:
a dashboard display configured to receive costs and parameters as input, and display scenarios; a data storage device; and an optimization engine communicatively coupled to the data storage device and the dashboard display, the optimization engine configured to execute an simulator module that when executed:
receives, via the dashboard display, a plurality of costs;
receives, via the dashboard display, parameters for building at least two scenarios, the parameters including at least a zoning policy, a routing policy, and a base algorithm;
creates the at least two scenarios based on the parameters;
receives, via the dashboard display, at least one identifier to associate with the at least two scenarios;
executes scenario simulations for the at least one identifier based on the at least two scenarios and the plurality of costs, wherein the scenario simulations generates scenario information associated with the at least one identifier;
selects a best scenario from the at least two scenarios based on the scenario information; and
in response to selection of the best scenario, configures a computing system associated with the at least one identifier to execute a zoning policy, a routing policy, and a base algorithm policy associated with the best scenario,
wherein the computing system executes the zoning policy, the routing policy, and the base algorithm policy to fulfill orders.

2 . The system of claim 1 , wherein the scenario information includes one or more of a pick rate, a distance per item, a total distance, a walk time, a retrieval time, a seek time, a consolidation time, a total time, items per tote, and total totes for the at least one identifier.

3 . The system of claim 1 , the simulator module, when executed, further configured to:
create one or more additional scenarios based on additional parameters entered by the user; and execute additional scenario simulations on the at least one identifier based on the one or more additional scenarios.

4 . The system of claim 1 , the simulator module, when executed, further configured to display scenarios and a comparison between the scenario information generated by the scenario simulations.

5 . The system of claim 1 , wherein the costs includes one or more of a walking cost, a retrieval cost, a consolidation cost, and a consolidation space cost.

6 . The system of claim 1 , further comprising a global integrated fulfillment system configured to provide the optimization engine with orders.

7 . The system of claim 1 , wherein the scenario simulations are performed using historical orders made during a specified time period.

8 . The system of claim 1 , wherein the scenario simulations are performed using recently received orders to be fulfilled.

9 . A method comprising:
receiving, via an optimization engine communicatively coupled to a dashboard display configured to receive costs and parameters as input, a plurality of costs entered into the dashboard display; receiving, via the optimization engine, parameters entered into the dashboard display for building at least two scenarios, the parameters including at least a zoning policy, a routing policy, and a base algorithm policy; creating, via the optimization engine, the at least two scenarios based on the parameters; receiving, via the optimization engine, at least one identifier entered into the dashboard display to associate with the at least two scenarios; executing, via the optimization engine, scenario simulations for the at least one identifier based on the at least two scenarios and the plurality of costs, wherein the scenario simulations generate scenario information associated with the at least one identifier; selecting, via the optimization engine, a best scenario from the at least two scenarios based on the scenario information; and in response to selection of the best scenario, configuring, via the optimization engine, a computing system associated with the at least one identifier to execute a zoning policy, a routing policy, and a base algorithm policy associated with the best scenario, wherein the computing system executes the zoning policy, the routing policy, and the base algorithm policy to fulfill orders.

10 . The method of claim 9 , wherein the pick information includes one or more of a pick rate, a distance per item, a total distance, a walk time, a retrieval time, a seek time, a consolidation time, a total time, items per tote, and total totes for the at least one store.

11 . The method of claim 9 , further comprising:
creating, by the optimization engine, one or more additional scenarios based on additional parameters entered by the user; and executing, by the optimization engine, additional scenario simulations on the at least one identifier based on the one or more additional scenarios.

12 . The method of claim 9 , further comprising displaying a comparison between the pick information generated by the scenario simulations.

13 . The method of claim 9 , wherein the costs includes one or more of a walking cost, a retrieval cost, a consolidation cost, and a consolidation space cost.

14 . The method of claim 9 , further comprising a global integrated fulfillment system configured to provide the optimization engine with orders.

15 . The method of claim 9 , further comprising executing, via the optimization engine, the scenario simulations using historical orders made during a specified time period.

16 . The method of claim 9 , further comprising executing, via the optimization engine, the scenario simulations using recently received orders to be fulfilled.

Assignees

• Walmart Apollo Llc

Inventors

• Rajkhowa Pratosh Deepak
• Shendre Ameya Ajay

Classifications

• G06Q10/047

  Optimisation of routes or paths, e.g. travelling salesman problem · CPC title

• G06Q10/087 Primary

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

• G06Q10/06316

  Sequencing of tasks or work · CPC title