Incentive allocation method balances budget and profit in real time
Large-Scale Trade-Off Curve Computation for Incentive Allocation with Cardinality and Matroid Constraints
Data Structures and Algorithms
Summary
The paper deals with how to assign incentives like coupons to many users efficiently while considering limits on coupon assignments for each user. The authors handle complex limits using a math concept called matroids, ensuring the assignments respect these rules. They show a way to keep track of the trade-off between spending budget and earning profit quickly, even on a large scale. This approach helps businesses dynamically manage incentives without breaking constraints.
What this means in practice
- •For mobile app developers: efficiently manage user coupons in ride-sharing or delivery apps while respecting user-specific coupon limits.
- •For online advertising teams: dynamically allocate advertising incentives under complex constraints to maximize profit without overspending budgets.
Authors
Yu Cong, Chao Xu, Yi Zhou
Abstract
We consider a large-scale incentive allocation problem where the entire trade-off curve between budget and profit has to be maintained approximately at all times. The application originally comes from assigning coupons to users of ride-sharing apps, where each user can have a limit on the number of coupons assigned to them. We consider a more general form, where the coupons for each user form a matroid, and the set of coupons assigned to each user must be an independent set. We show the entire trade-off curve can be maintained approximately in near real time.