Dynamic Pricing and Matching for Two-Sided Queues
研究共享经济和在线市场中的双边排队系统，提出基于阈值的两价格策略和基于队长最大权匹配策略，实现近似最优利润，并分析大规模和大市场情形下的最优性条件。
Motivated by applications from gig economy and online marketplaces, we study a two-sided queueing system under joint pricing and matching controls. The queueing system is modeled by a bipartite graph, where the vertices represent customer or server types and the edges represent compatible customer-server pairs. We propose a threshold-based two-price policy and queue length-based maximum-weight matching policy and show that it achieves a near-optimal profit. We study the system under the large-scale regime, wherein the arrival rates are scaled up, and under the large-market regime, wherein both the arrival rates and numbers of customer and server types increase. We show that two-price policy is a primary driver for optimality in the large-scale regime. We demonstrate the advantage of maximum-weight matching with respect to the number of customer and server types. Concurrently, we show that the interplay of pricing and matching is crucial for optimality in the large-market regime.