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This paper proposes a fairness-aware pricing framework for retail food products using Autoregressive Distributed Lag (ARDL) models for sales forecasting and optimizes prices with Linear Programming and Simulated Annealing under CPI-based bounds to prevent consumer exploitation.
This paper presents Quota Marketplace, a market-based dynamic pricing mechanism deployed at Google for efficient allocation of ML training accelerators across business units, achieving Pareto efficiency and max-min fairness under heterogeneous workload values.
The paper introduces Human-in-the-Loop Gated Bandit (HITL-GB) for short-term rental dynamic pricing, showing that historical pricing data under a prior policy is structurally equivalent to on-policy warm-up data, reducing cold-start from ~150 to ~30 episodes.