We consider the online stochastic matching problem for bipartite graphs where edges adjacent to an online node must be probed to determine if they exist, based on known edge probabilities. Our algorithms respect commitment, in that if a probed edge exists, it must be used in the matching. We study this matching problem subject to a downward-closed constraint on each online node's allowable edge probes. Our setting generalizes the commonly studied patience (or time-out) constraint which limits the number of probes that can be made to an online node's adjacent edges. We introduce a new LP that we prove is a relaxation of an optimal offline probing algorithm (the adaptive benchmark) and which overcomes the limitations of previous LP relaxations. (1) A tight $\frac{1}{2}$ ratio when the stochastic graph is generated from a known stochastic type graph where the $t^{th}$ online node is drawn independently from a known distribution $\scr{D}_{\pi(t)}$ and $\pi$ is chosen adversarially. We refer to this setting as the known i.d. stochastic matching problem with adversarial arrivals. (2) A $1-1/e$ ratio when the stochastic graph is generated from a known stochastic type graph where the $t^{th}$ online node is drawn independently from a known distribution $\scr{D}_{\pi(t)}$ and $\pi$ is a random permutation. We refer to this setting as the known i.d. stochastic matching problem with random order arrivals. Our results improve upon the previous best competitive ratio of $0.46$ in the known i.i.d. setting against the standard adaptive benchmark. Moreover, we are the first to study the prophet secretary matching problem in the context of probing, where we match the best known classical result.
翻译:我们考虑双节点图的在线随机匹配问题, 需要根据已知的边缘概率来检测是否存在。 我们的算法尊重承诺, 如果发现边缘存在, 就必须在匹配中使用。 我们的设置一般化了共同研究的耐心( 或超时) 限制, 从而限制可以进行在线节点的边缘 。 我们引入了一个新的 LP, 这证明是最佳的离线算法( 适应性基准) 的放松, 并且克服了先前 LP 放松的局限性 。 (1) 当每个在线节点的允许边缘探测器生成了一种向下封闭的制约 。 我们设置了一个已知的 stochaster 类型图时, 美元在线节点与已知的发行量 美元 =crcr{D} 相邻端边缘 。 我们引入了一个新的 LP, 这证明我们是一个最佳的离线值 road comproprebal combal complia( 基准), 并且我们从已知的 i- drodeal deal develop rideal deal develop ride ralal destal demod.