Allocation Quantity Setting for Food Delivery Restrictions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing food delivery systems struggle to accurately determine and manage order quantities that satisfy various restrictions, such as dietary limitations or allergies, leading to inefficiencies in product distribution.
Innovation Solution
An information processing system that includes a server and terminal devices, capable of acquiring user information, product information, and restrictions to set allocation quantities based on priority degrees and conditions, presenting alternative products if necessary, to ensure distribution quantities meet user demands while adhering to restrictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If order quantities are determined without considering user restrictions and demand conditions, then the ordering process is simple and quick, but the distribution quantity cannot satisfy user restrictions and may lead to food waste or insufficient allocation
Solution Approach 1:
The order quantity determination process is segmented into distinct components: acquiring user information with restrictions and demand conditions, acquiring product information, calculating allocation quantities for each user based on their specific conditions, and determining the total order quantity. This segmentation allows the system to handle complex restrictions systematically without overwhelming complexity.
Solution Approach 2:
User information including restrictions and demand conditions is acquired and stored before the actual ordering process. This preliminary action enables the system to quickly calculate appropriate allocation quantities during ordering without requiring complex real-time negotiations or adjustments, thus improving reliability while maintaining operational efficiency.
2Measurement precision
If allocation quantities are calculated based on detailed user conditions and restrictions, then distribution accuracy is improved, but the processing time and computational resources increase
Solution Approach 1:
User information including restrictions and demand conditions is acquired and stored in advance before the ordering process. This preliminary preparation enables the server to quickly retrieve and process this information when an order is placed, reducing the computational burden during the actual ordering moment while maintaining high precision in allocation quantity calculation.
Solution Approach 2:
The system automatically calculates allocation quantities based on pre-stored user conditions and product information without requiring manual intervention or complex real-time negotiations. This self-service approach maintains high measurement precision while minimizing processing time and computational resource usage.
3Adaptability or versatility
If the system presents multiple product options and allocation quantities to users, then user satisfaction and restriction compliance improve, but the ease of operation decreases
Solution Approach 1:
The server automatically calculates and presents allocation quantities based on pre-acquired user information and product details. This self-service approach allows the system to adapt to diverse user needs by considering their specific restrictions and demand conditions, while simultaneously maintaining ease of operation by eliminating the need for users to manually calculate or negotiate allocation quantities.
Solution Approach 2:
The system presents the calculated allocation quantity to the user for confirmation. This feedback mechanism allows users to review and verify that their restrictions and demands are properly reflected in the allocation, enhancing adaptability while maintaining operational simplicity through automated calculation.
4Productivity
If the system automatically determines order quantities without user input, then processing efficiency increases, but the ability to accurately reflect user preferences decreases
Solution Approach 1:
User information including restrictions and demand conditions is acquired and stored in advance through user profiles or previous interactions. This preliminary action enables the server to automatically determine order quantities with high efficiency while accurately reflecting user preferences, as the preference data is already captured and structured for quick processing.
Solution Approach 2:
The system presents the automatically calculated allocation quantity to the user for verification. This feedback loop ensures that user preferences are accurately reflected while maintaining processing efficiency, as most calculations are done automatically but can be reviewed and adjusted by the user if needed.
Data Source
AI summary
An information processing system including a server device and a terminal device presents a proposed meal based on user input. The server device and terminal device do this by acquiring an order request, order quantity information and user identification information for a user. The server device acquires product information, user information including a first condition as a restriction condition of the user. The server device sets an allocation quantity of the order product based on the first condition and causes the terminal device to present the set allocation quantity of the order product to the user. In some embodiments, the user information includes a second condition which is a demand condition of the user.