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

Abstract

A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform: receiving a plurality of orders comprising one or more items associated with a plurality of retail stores; separating the plurality of orders by a plurality of load numbers; generating, using an optimization algorithm, a plurality of rebatched orders; sorting the one or more items within the plurality of rebatched orders by sequence numbers; and transmitting the one or more items within the plurality of rebatched orders, as sorted, to a plurality of user devices for filling each respective one of the number of containers with the one or more items within the plurality of rebatched orders. Other embodiments are described.

What is claimed: 
     
         1 . A system comprising:
 one or more processors; and   one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform:
 receiving a plurality of orders comprising one or more items associated with a plurality of retail stores; 
 separating the plurality of orders by a plurality of load numbers, wherein each load number of the plurality of load numbers is associated with (i) a respective weight and (ii) a respective due time; 
 batching the plurality of orders by different commodities; 
 generating, using an optimization algorithm, a plurality of rebatched orders based at least in part on both a respective distance and a respective item volume of each respective item of the one or more items within each of the plurality of orders batched by the different commodities; 
 sorting the one or more items within the plurality of rebatched orders by sequence numbers based on at least a respective container volume of each respective one of a number of containers; and 
 transmitting the one or more items within the plurality of rebatched orders, as sorted, to a plurality of user devices of a plurality of users for filling each respective one of the number of containers with the one or more items within the plurality of rebatched orders. 
   
     
     
         2 . The system of  claim 1 , wherein receiving the plurality of orders further comprises:
 using an item locator system of a server computing device, wherein the server computing device is configured to communicate with the plurality of user devices of the plurality of users associated with the plurality of retail stores.   
     
     
         3 . The system of  claim 1 , wherein the sequence numbers are used by the plurality of users to retrieve the one or more items within the plurality of rebatched orders. 
     
     
         4 . The system of  claim 1 , wherein the computing instructions, when executed on the one or more processors, further cause the one or more processors 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 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 respective trolley used. 
   
     
     
         5 . The system of  claim 1 , wherein the computing instructions, when executed on the one or more processors, further cause the one or more processors 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 users to fill the number of containers; and 
   finding a set sol={P 1 , P 2  . . . P n } such that Σ p∈sol  C(P) is minimized where C(P) represents a respective cost of picking each item of the one or more items.   
     
     
         6 . The system of  claim 1 , wherein the computing instructions, when executed on the one or more processors, further cause the one or more processors to perform:
 storing, in a database, 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;   generating, by a map generation system, each respective map of a plurality of maps, wherein each respective map is overlaid with respective graphical icons of each respective item of the one or more items of the plurality of orders, wherein the database further stores the plurality of maps for the plurality of retail stores, wherein each respective map of the plurality of maps are associated with a respective retail store of the plurality of retail stores, and wherein each respective map of the plurality of maps is processed into a respective scalable vector graphic;   receiving, by a server computing device, a request for a particular map for a particular retail location of the plurality of retail stores; and   sending, by the map generation system, an image of the particular map, as requested, to a user device of the plurality of user devices, wherein the image of the particular map comprises an overlay of respective graphical icons of the one or more items and a respective pick path for the one or more items of the plurality of orders.   
     
     
         7 . The system of  claim 1 , wherein the computing instructions, when executed on the one or more processors, further cause the one or more processors to perform:
 defining every order O n {I 1 , I 2  . . . I n } of the plurality of orders 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 users to fill the number of containers, and each I represents a respective item of the one or more items; and 
   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 volume of a container.   
     
     
         8 . The system of  claim 1 , wherein the optimization algorithm is based on smart order batching. 
     
     
         9 . The system of  claim 1 , wherein the optimization algorithm is based on either one of volumetrics or split volumetrics. 
     
     
         10 . The system of  claim 1 , where in the optimization algorithm is based on either one of parallel picking or parallel picking with volumetrics. 
     
     
         11 . A method being implemented via execution computing instructions configured to run on one or more processors and stored at one or more non-transitory computer-readable media, the method comprising:
 receiving a plurality of orders comprising one or more items associated with a plurality of retail stores;   separating the plurality of orders by a plurality of load numbers, wherein each load number of the plurality of load numbers is associated with (i) a respective weight and (ii) a respective due time;   batching the plurality of orders by different commodities;   generating, using an optimization algorithm, a plurality of rebatched orders based at least in part on both a respective distance and a respective item volume of each respective item of the one or more items within each of the plurality of orders batched by the different commodities;   sorting the one or more items within the plurality of rebatched orders by sequence numbers based on at least a respective container volume of each respective one of a number of containers; and   transmitting the one or more items within the plurality of rebatched orders, as sorted, to a plurality of user devices of a plurality of users for filling each respective one of the number of containers with the one or more items within the plurality of rebatched orders.   
     
     
         12 . The method of  claim 11 , wherein receiving the plurality of orders further comprises:
 using an item locator system of a server computing device, wherein the server computing device is configured to communicate with the plurality of user devices of the plurality of users associated with the plurality of retail stores.   
     
     
         13 . The method of  claim 11 , wherein the sequence numbers are used by the plurality of users to retrieve the one or more items within the plurality of rebatched orders. 
     
     
         14 . The method of  claim 11 , 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 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 respective trolley used. 
   
     
     
         15 . The method of  claim 11 , further comprising:
 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 users to fill the number of containers; and 
   finding a set sol={P 1 , P 2  . . . P n } such that Σ p∈sol  C(P) is minimized where C(P) represents a respective cost of picking each item of the one or more items.   
     
     
         16 . The method of  claim 11 , further comprising:
 storing, in a database, 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;   generating, by a map generation system, each respective map of a plurality of maps, wherein each respective map is overlaid with respective graphical icons of each respective item of the one or more items of the plurality of orders, wherein the database further stores a plurality of maps for the plurality of retail stores, and wherein each map of the plurality of maps are associated with a respective retail store of the plurality of retail stores, and wherein each respective map of the plurality of maps is processed into a respective scalable vector graphic;   receiving, by a server computing device, a request for a particular map for a particular retail location of the plurality of retail stores; and   sending, by the map generation system, an image of the particular map, as requested, to a user device of the plurality of user devices, wherein the image of the particular map comprises an overlay of respective graphical icons of the one or more items and a respective pick path for the one or more items of the plurality of orders.   
     
     
         17 . The method of  claim 11 , further comprising:
 defining every order O n ={I 1 , I 2  . . . I n } of the plurality of orders 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 users to fill the number of containers, and each I represents a respective item of the one or more items; and 
   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 volume of a container.   
     
     
         18 . The method of  claim 11 , wherein the optimization algorithm is based on smart order batching. 
     
     
         19 . The method of  claim 11 , wherein the optimization algorithm is based on either one of volumetrics or split volumetrics. 
     
     
         20 . The method of  claim 11 , where in the optimization algorithm is based on either one of parallel picking or parallel picking with volumetrics.