An o2o to home service order fusion method and system considering space-time constraints
By using a two-layer greedy order fusion algorithm and Shapley value cost allocation, O2O home delivery service orders are merged, solving the problems of high worker opportunity cost and sparse demand distribution. This achieves low-cost and efficient order fusion and promotes the popularization of O2O home delivery services.
CN116777558BActive Publication Date: 2026-06-19TIANJIN UNIV
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TIANJIN UNIV
- Filing Date
- 2023-06-26
- Publication Date
- 2026-06-19
AI Technical Summary
Technical Problem
In O2O home delivery services, the opportunity cost of workers going out to provide services is high, resulting in high service prices and sparse demand distribution, which affects users' willingness to buy.
Method used
A two-layer greedy order fusion algorithm is adopted to merge geographically dispersed orders and merge orders across QoS levels. The Shapley value is used to allocate costs and optimize order allocation and cost accounting.
Benefits of technology
This reduces the service cost per order, increases the number of orders a worker can complete per trip, meets diverse customer needs, and promotes industry prosperity.
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Smart Images
Figure CN116777558B_ABST
Abstract
This invention discloses an O2O home delivery service order fusion method and system that considers spatiotemporal constraints. It proposes to merge several geographically dispersed orders into a single fused order, and then assign a worker to each fused order. This allows the opportunity cost of the worker's trip to be shared among the sub-orders within a fused order. For cross-QoS level fused orders, orders that are spatially close but have different QoS requirements are grouped together. The order with the highest QoS requirement in the group determines the skill level of the worker assigned to that fused order, thereby increasing the number of orders a worker can complete per trip. This method reduces the service cost per order, enabling more customers to enjoy home delivery services, while also considering the QoS levels of home delivery services to meet diverse customer needs and accelerate the prosperity of the home delivery service industry.
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