System for improving in-store picking performance and experience by optimizing tote-fill and order batching of items in retail store and method of using same
A system and method includes receiving a plurality of orders having one or more items, separating the orders by load number and due times, batching the separate orders into different commodities, generate optimized rebatched orders according to an optimization algorithm that generates the optimized rebatched orders based on at least one of distance and volume of the items of the one or more items within the batched orders of the different commodities, sorting the one or more items within the rebatched orders by sequence numbers, and transmitting the sorted one or more items to a user device.
1. A system comprising:
a server computing device comprising one or more processors, the server computing device being configured to provide output to a plurality of first user devices of a plurality of first users, wherein the plurality of first users comprise workers at a plurality of retail stores, the server computing device being further configured to communicate with the plurality of first user devices and a plurality of second user devices and to perform:
receiving, using an item locator system of the server computing device, a plurality of orders having one or more items, wherein the plurality of orders are received from the plurality of second user devices of a plurality of customers, and wherein the plurality of orders are associated with the plurality of retail stores;
separating, by the one or more processors of the server computing device, the plurality of orders by a plurality of vehicle load numbers, wherein each vehicle load number of the plurality of the vehicle load numbers is associated with a weight and a due time;
batching, by the one or more processors of the server computing device, the plurality of orders, as separated, into different commodities, wherein the different commodities comprise different temperatures of the one or more items;
generating, by the one or more processors of the server computing device, rebatched orders according to an optimization algorithm that generates the rebatched orders based at least in part on both a distance and a first volume of each respective item of the one or more items within each of the rebatched orders of the different commodities;
sorting, by the one or more processors of the server computing device, the one or more items within the rebatched orders by sequence numbers based on at least a second volume of a container of each respective one of a number of containers to be used by the plurality of first users to retrieve the one or more items of each of the rebatched orders; and
sending instructions, by the one or more processors of the server computing device, to display on user interfaces of the plurality of first user devices information for filling the each respective one of the number of containers with the one or more items of each of the rebatched orders.
2. The system of claim 1 , wherein the server computing device is further configured to perform:
defining a pick-walk P as a function of total capacity of a trolley as:
P={T 1 ,T 2 . . . T n }N≤K,
where each T represents a respective trolley used by a respective one of the plurality of first users to fill the number of containers, N represents a number of the one or more items, and K is a total capacity of the trolley used.
3. The system of claim 1 , wherein the server computing device is further configured to perform:
defining an item-set I P corresponding to a pick-walk P as:
I∈I P if I∈T i for all T i ∈P,
where I represents an item of the one or more items, and T represents a trolley used by one of the plurality of first users to fill the number of containers.
4. The system of claim 1 , wherein the server computing device is further configured to perform:
storing, in a database of the server computing device, map data of the one or more items located in a retail store of the plurality of retail stores associated with a map of the retail store, wherein the database further stores a plurality of maps for the plurality of retail stores.
5. The system of claim 1 , wherein the server computing device is further configured to perform:
defining every order O n {I 1 , I 2 . . . I n } as:
O n ={T 1 ,T 2 . . . T n } where, T 1 ∪T 2 ∪ . . . T n =O n and T i ∩T j =Ø, ∀T i ,T j ∈O n ,
where O n represents a respective one of the plurality of orders, each T represents a respective trolley used by a respective one of the plurality of first users to fill the number of containers, and each I represents a respective item of the one or more items.
6. The system of claim 1 , wherein the server computing device is further configured to perform:
finding disjoint sets T i s so that ΣV i ≤C is minimized,
wherein, T i s represents disjoint sets, V i is a volume of I 1 , I 1 represents an item of the one or more items, and C is a total second volume of the container.
7. The system of claim 1 , wherein the optimization algorithm is based on smart order batching.
8. The system of claim 1 , wherein the optimization algorithm is based on either one of volumetrics or split volumetrics.
9. The system of claim 1 , the optimization algorithm is based on either one of parallel picking or parallel picking with volumetrics.
10. A method comprising:
providing, by a server computing device comprising one or more processors, output to a plurality of first user devices of a plurality of first users, wherein the plurality of first users comprise workers at a plurality of retail stores, and wherein the server computing device being configured to communicate with the plurality of first user devices and a plurality of second user devices;
receiving, by an item locator system of the server computing device, a plurality of orders having one or more items, wherein the plurality of orders are received from the plurality of second user devices of a plurality of customers, and wherein the plurality of orders are associated with the plurality of retail stores;
separating, by the one or more processors of the server computing device, the plurality of orders by a plurality of vehicle load numbers, wherein each vehicle load number of the plurality of the vehicle load numbers is associated with a weight and a due time;
batching, by the one or more processors of the server computing device, the plurality of orders, as separated, into different commodities, wherein the different commodities comprise different temperatures of the one or more items;
generating, by the one or more processors of the server computing device, rebatched orders according to an optimization algorithm that generates the rebatched orders based at least in part on both a distance and a first volume of each respective item of the one or more items within each of the rebatched orders of the different commodities;
sorting, by the one or more processors of the server computing device, the one or more items within the rebatched orders by sequence numbers based on at least a second volume of a container of each respective one of a number of containers to be used by the plurality of first users to retrieve the one or more items of each of the rebatched orders; and
sending instructions, by the one or more processors of the server computing device, to display on user interfaces of the plurality of first user devices information for filling the each respective one of the number of containers with the one or more items of each of the rebatched orders.
11. The method of claim 10 , further comprising:
defining a pick-walk P as a function of total capacity of a trolley as:
P={T 1 ,T 2 . . . T n }N≤K,
where each T represents a respective trolley used by a respective one of the plurality of first users to fill the number of containers, N represents a number of the one or more items, and K is a total capacity of the trolley used.
12. The method of claim 10 , further comprising:
defining an item-set I P corresponding to a pick-walk P as:
I∈IP if I∈T i for all T i ∈P,
where I represents an item of the one or more items, and T represents a trolley used by one of the plurality of first users to fill the number of containers.
13. The method of claim 10 , further comprising:
storing, in a database of the server computing device, map data of the one or more items located in a retail store of the plurality of retail stores associated with a map of the retail store, wherein the database further stores a plurality of maps for the plurality of retail stores.
14. The method of claim 10 , further comprising:
finding a set sol={P 1 , P 2 . . . P n } such that Σ p∈sol C(P) is minimized.
15. The method of claim 13 , further comprising:
defining every order O n . . . {I 1 , I 2 . . . I n } as:
O n ={T 1 ,T 2 . . . T n } where, T 1 ∪T 2 ∪ . . . T n =O n and T i ∩T j =Ø, ∀T i ,T j ∈O n ,
where O n represents a respective one of the plurality of orders, each T represents a respective trolley used by a respective one of the plurality of first users to fill the number of containers, and each I represents a respective item of the one or more items.
16. The method of claim 10 , further comprising:
finding disjoint sets T i s so that Σ i∈T V i ≤C is minimized,
wherein, T i s represents disjoint sets, V i is a volume of I 1 , I 1 represents an item of the one or more items, and C is a total second volume of the container.
17. The method of claim 10 , wherein the optimization algorithm is based on smart order batching.
18. The method of claim 10 , wherein the optimization algorithm is based on either one of volumetrics or split volumetrics.
19. The method of claim 10 , wherein the optimization algorithm is based on either one of parallel picking or parallel picking with volumetrics.
20. One or more non-transitory computer-readable storage media, having computer-executable instructions embodied thereon, wherein when executed by at least one processor, the computer-executable instructions cause the processor to:
provide output to a plurality of first user devices of a plurality of first users, wherein the plurality of first users comprise workers at a plurality of retail stores, and wherein a server computing device being configured to communicate with the plurality of first user devices and a plurality of second user devices;
receive a plurality of orders having one or more items, wherein the plurality of orders are received from the plurality of second user devices of a plurality of customers, and wherein the plurality of orders are associated with the plurality of retail stores;
separate the plurality of orders by a plurality of vehicle load numbers, wherein each vehicle load number of the plurality of the vehicle load numbers is associated with a weight and a due time;
batch the plurality of orders, as separated, into different commodities, wherein the different commodities comprise different temperatures of the one or more items;
generate rebatched orders according to an optimization algorithm that generates the rebatched orders based at least in part on both a distance and a first volume of each respective item of the one or more items within each of the rebatched orders of the different commodities;
sort the one or more items within the rebatched orders by sequence numbers based on at least a second volume of a container of each respective one of a number of containers to be used by the plurality of first users to retrieve the one or more items of each of the rebatched orders; and
sending instructions to display on user interfaces of the plurality of first user devices information for filling the each respective one of the number of containers with the one or more items of each of the rebatched orders.