Retail Order Batching Using Item Location Coordinates
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Solution Overview
Problem
Current in-store picking systems are inefficient due to the use of static sequence numbers for order fulfillment, leading to suboptimal pick paths and inefficient use of manpower in retail stores, as they do not leverage exact item location information for optimizing order batching and pick paths.
Innovation Solution
A system and method that utilize (X, Y) coordinates to generate optimized pick paths within retail stores by separating orders by load number and due times, and using a computing device to create an optimized pick path based on item location, which is then displayed on a user device overlaid on a store map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static sequence numbers are used for order fulfillment, then the picking process is simple to implement, but the pick paths are suboptimal and travel distance increases
Solution Approach 1:
The system transitions from static sequence numbers to dynamic optimization by using real-time location data (X, Y coordinates) and store layout information to generate optimized pick paths that adapt to actual item positions, thereby improving picker efficiency without sacrificing operational simplicity
Solution Approach 2:
The invention changes the parameter basis for picking from abstract sequence numbers to concrete spatial coordinates (X, Y locations), enabling the system to calculate optimal routes based on actual physical distances and store geometry, thus reducing travel distance while maintaining ease of implementation through computational optimization
2Device complexity
If global integrated fulfillment systems batch orders with static constraints, then order batching is manageable, but travel time and distance for pickers increase
Solution Approach 1:
The system performs preliminary optimization by pre-calculating optimized pick paths based on item locations, store layouts, and order batching requirements before pickers begin their work, thereby reducing actual travel time during the picking process while maintaining manageable order batching complexity
Solution Approach 2:
The invention introduces an intermediary optimization layer between order batching and actual picking, using computational algorithms to generate optimized routes that mediate between the constraints of batched orders and the physical realities of store layouts, thus reducing travel time without increasing batching complexity
3Ease of operation
If sequence numbers are used to identify pick sequence, then order fulfillment is straightforward, but exact item location information is not utilized for optimization
Solution Approach 1:
The system adds a spatial dimension to the picking process by incorporating X, Y coordinates and store layout geometry into the optimization algorithm, transforming the one-dimensional sequence number approach into a two-dimensional spatial optimization problem, thereby enabling precise location-based routing while maintaining straightforward order fulfillment
Data Source
AI summary
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, generating an optimized pick path through a retail store to pick the one or more items according to an optimization algorithm that generates the optimized pick path based on item location of the one or more items within the batched orders of the different commodities, obtaining a store map, the store map being indicative of a layout of the retail store, transmitting a representation of the store map and the optimized pick path to the user device, and displaying the store map overlaid with the optimized pick path on a graphical display of the user device.