HMAF: New Framework Optimizes Ad Allocation Between Guaranteed Delivery and Real-Time Bidding
Researchers from Meituan have introduced HMAF, a hierarchical framework that unifies Guaranteed Delivery contract fulfillment and Real-Time Bidding auction optimization in online advertising platforms. Prior approaches typically handled these two systems separately or relied on heuristic rules, leaving a gap between short-term revenue and long-term contract obligations. The framework was deployed at Meituan and achieved a 3.72% improvement in GD delivery rate and a 1.59% increase in total ad revenue.
HMAF (Hierarchical Multi-Slot Allocation Framework) is a unified system designed to address the tension between Guaranteed Delivery (GD) advertising contracts—which promise fixed impression volumes to advertisers—and Real-Time Bidding (RTB) auctions that maximize immediate revenue. The framework is structured around a Plan–Calibrate–Execute paradigm, combining offline constraint optimization for GD resource planning, dynamic calibration of GD–RTB competitiveness, and real-time listwise ranking decisions across multi-slot ad environments. Existing methods either decouple the two systems or apply heuristic priority rules, which the authors argue fail to balance short-term revenue with long-term delivery guarantees under complex multi-slot constraints. HMAF was implemented across multiple marketing scenarios at Meituan, one of the world's largest online food delivery platforms, yielding measurable gains in both contract fulfillment and overall advertising revenue. The paper has been accepted to the KDD 2026 Applied Data Science Track, indicating peer review by the applied machine learning and data mining community.
What's missing
The paper does not detail the baseline systems against which HMAF was compared, the duration or scale of the live deployment experiments, or whether the reported gains generalize beyond Meituan's specific platform architecture. Potential trade-offs—such as effects on advertiser fairness, auction dynamics, or edge cases where GD and RTB objectives conflict severely—are not discussed in the abstract.
What different sources said
- arXiv cs.LGCenter
HMAF: A Hierarchical Multi-Slot GD-RTB Allocation Framework
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