We study a continuous and infinite time horizon counterpart to the classic prophet inequality, which we term the stationary prophet inequality problem. Here, copies of a good arrive and perish according to Poisson point processes. Buyers arrive similarly and make take-it-or-leave-it offers for unsold items. The objective is to maximize the (infinite) time average revenue of the seller. Our main results are pricing-based policies which (i) achieve a $1/2$-approximation of the optimal offline policy, which is best possible, and (ii) achieve a better than $(1-1/e)$-approximation of the optimal online policy. Result (i) improves upon bounds implied by recent work of Collina et al. (WINE'20), and is the first optimal prophet inequality for a stationary problem. Result (ii) improves upon a $1-1/e$ bound implied by recent work of Aouad and Sarita\c{c} (EC'20), and shows that this prevalent bound in online algorithms is not optimal for this problem.
翻译:我们研究的是与经典先知不平等相对应的连续和无限的时间范围,我们称之为固定先知不平等问题。这里,根据Poisson点的流程,好到好、坏的复制件。买家同样到来,对未售物品提出接受或放弃报价。目标是最大限度地增加卖方(无限)时间平均收入。我们的主要结果是基于定价的政策,即(一) 实现最佳离线政策1/2美元,这是最好的办法;(二) 实现比最佳在线政策1-1/e美元更好的办法。结果(一) 改进了Collina等人最近的工作(WINE'20)所暗示的界限,是解决固定问题的第一个最佳办法。结果(二) 改进了Aouad和Sarita\c{c}(EC'20)最近的工作所隐含的1-1/e美元约束值,并表明网上算法中的这一普遍约束不是解决问题的最佳办法。