Delivery Order Batching With Permutation Ranking for QSR Dispatch
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Quick-service restaurants (QSRs) face challenges in efficiently managing delivery orders due to their finite workforce, leading to inefficiencies in order fulfillment and reduced customer satisfaction and food quality, as existing methods fail to account for delivery person-specific factors and dynamic scaling of workforces.
Innovation Solution
A batching system that generates optimized batches of delivery orders by simulating permutations based on total delivery time, promise time miss, and hold time miss, considering delivery person data and food quality, and prioritizes orders with explicit delivery times over ASAP expectations, ensuring efficient workload distribution and food quality preservation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If QSRs use third-party delivery services to fulfill delivery orders, then delivery capacity and workforce scalability are improved, but delivery costs and loss of quality control increase
Solution Approach 1:
The system dynamically optimizes delivery permutations based on real-time factors including delivery person locations, traffic conditions, order priorities, and time windows. The batching system continuously recalculates optimal delivery sequences to adapt to changing conditions, enabling efficient use of fixed workforce while maintaining scalability comparable to third-party services.
2Adaptability or versatility
If QSRs use third-party delivery services, then workforce scalability is improved, but quality control over customer experiences deteriorates
Solution Approach 1:
The system incorporates feedback loops that continuously monitor delivery performance metrics, customer satisfaction data, and food quality indicators. This feedback is used to refine batching decisions and optimize delivery assignments, ensuring consistent quality control while maintaining operational flexibility and scalability.
3Loss of energy
If QSRs use their own employees for delivery operations, then delivery costs are reduced and quality control is improved, but workforce scalability and ability to meet demand deteriorates
Solution Approach 1:
The system performs preliminary batching and route optimization before delivery operations begin. By pre-calculating optimal delivery sequences and assignments based on forecasted demand and current workforce availability, the system enables fixed employees to handle variable demand volumes efficiently, achieving scalability without requiring dynamic hiring.
4Reliability
If QSRs use their own employees for delivery, then quality control is improved, but ability to dynamically scale workforce to meet demand deteriorates
Solution Approach 1:
The system changes operational parameters such as delivery batch sizes, route sequences, and assignment priorities based on real-time demand conditions. By optimizing these parameters rather than workforce size, the system maintains quality control through consistent processes while adapting to varying demand levels with a fixed employee base.
Data Source
AI summary
Embodiments of the present disclosure relate to a system and method for order batching. An example method includes receiving a plurality of orders for delivery to a plurality of destinations; generating permutations of the orders corresponding to different sequences of the destinations; estimating, for the permutations, one or more of a total delivery time, a total promise time miss, and a total hold time miss; generating batch scores for the permutations based on the respective total delivery time, total promise time miss, and total hold time miss; generating a permutation ranking based on the batch scores; determining a top-ranked permutation; assigning orders in the top-ranked permutation to one of a plurality of delivery persons; initiating preparation of the orders in response to determining that an estimated arrival interval of the delivery person is within an estimated preparation interval; and dispatching delivery of the orders to the delivery person.