Product Assignment System for Shared Shopping Lists
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Solution Overview
Problem
Existing shopping list applications do not effectively assign products from a shared shopping list to participating shoppers based on their characteristics and product parameters, leading to inefficient product retrieval and potential difficulties for shoppers with mobility or physical limitations.
Innovation Solution
A method that assigns products from a shared shopping list to shoppers by combining their characteristics, such as mobility and physical ability, with product parameters like location and placement, using a scoring system to optimize product assignments and ensure efficient retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If products are assigned from a shared shopping list without considering shopper characteristics, then the assignment process is simple, but shoppers with mobility or physical limitations experience difficulty retrieving products
Solution Approach 1:
The system changes the parameters of product assignment by incorporating shopper characteristics (mobility, physical ability) and product parameters (location, placement) into the assignment process. This transforms the simple assignment into an optimized assignment that considers multiple variables, improving ease of operation for shoppers with limitations while managing system complexity through automated scoring.
Solution Approach 2:
The system performs preliminary action by pre-calculating shopper characteristics and product parameters before the actual shopping trip. The scoring system is prepared in advance, and product assignments are optimized beforehand based on the calculated scores, ensuring that shoppers receive tailored assignments that accommodate their capabilities before they even enter the store.
2Productivity
If product assignments are optimized using shopper characteristics and product parameters, then retrieval efficiency is improved, but the processing time and computational resources increase
Solution Approach 1:
The system applies partial action by focusing on the most critical shopper characteristics and product parameters for optimization. Rather than analyzing every possible variable, the system identifies and scores the key factors (mobility, physical ability, location, placement) that have the greatest impact on retrieval efficiency, achieving good results without excessive processing time.
Solution Approach 2:
The system enables self-service by allowing shoppers to input their own characteristics and preferences, which are then automatically processed by the scoring system. The system serves itself by using predefined algorithms and criteria to automatically generate optimized assignments without requiring manual intervention, reducing processing time while maintaining efficiency.
3Duration of action of moving object
If all shoppers are assigned products simultaneously without optimization, then the assignment process is quick, but some shoppers may finish much earlier or later than others
Solution Approach 1:
The system introduces dynamics by creating flexible, adaptive product assignments based on real-time shopper characteristics. Rather than static assignments, the system dynamically adjusts which products are assigned to which shoppers based on their calculated scores, allowing for optimized trip durations that balance the workload across all shoppers and improve overall shopping efficiency.
Data Source
AI summary
A method of assigning products to shoppers can be provided by determining that a plurality of shoppers are collaborating with one another to purchase a plurality of products included on a shared shopping list, receiving shopper characteristics for the plurality of shoppers, receiving respective parameters for the plurality of products included on the shared shopping list, assigning respective sub-lists of the plurality of products for picking by respective ones of the shoppers at a retail shopping location based on the shopper characteristics for the respective ones of the shoppers and the respective parameters for the plurality of products included on the shared shopping list, and providing the respective sub-lists of the plurality of products to the plurality of shoppers. Related systems are also disclosed.