Weitzman introduced Pandora's box problem as a mathematical model of sequential search with inspection costs, in which a searcher is allowed to select a prize from one of $n$ alternatives. Several decades later, Doval introduced a close version of the problem, where the searcher does not need to incur the inspection cost of an alternative, and can select it uninspected. Unlike the original problem, the optimal solution to the nonobligatory inspection variant is proved to need adaptivity, and by recent work of [FLL22], finding the optimal solution is NP-hard. Our first main result is a structural characterization of the optimal policy: We show there exists an optimal policy that follows only two different pre-determined orders of inspection, and transitions from one to the other at most once. Our second main result is a polynomial time approximation scheme (PTAS). Our proof involves a novel reduction to a framework developed by [FLX18], utilizing our optimal two-phase structure. Furthermore, we show Pandora's problem with nonobligatory inspection belongs to class NP, which by using the hardness result of [FLL22], settles the computational complexity class of the problem. Finally, we provide a tight 0.8 approximation and a novel proof for committing policies [BK19] (informally, the set of nonadaptive policies) for general classes of distributions, which was previously shown only for discrete and finite distributions [GMS08].
翻译:Pandora Weitzman引入了Pandora的框问题,作为以检查成本相继搜索的数学模型,在其中,搜索者可以从一个美元替代方案中选择一个奖项。几十年后,Doval引入了一种近版的问题,搜索者不需要为另一个替代方案承担检查费用,而可以不经检查而选择。与最初的问题不同,对非强制性检查变异物的最佳解决办法证明需要适应性,而且根据[FLLL22]最近的工作,找到最佳的解决方案是NP-硬的。我们的第一个主要结果是对最佳政策进行结构性的定性:我们显示存在一种最佳政策,它遵循的是两种不同的预先确定的检查命令,并且最多一次从一个到另一个的过渡。我们的第二个主要结果是一个混合时间近似计划(PTAS ) 。 我们的证据是对[FLX18] 开发的框架进行新颖的缩减, 利用我们最佳的两阶段结构。此外,我们展示Pandora 问题与非强制性检查的问题属于一个等级的NPP,而后者只是使用不固定的精确分配政策[FL22] 的复杂度,而我们最后的精确的精确的分类的精确的分类, 解决了[FLIL22 的精确的精确的分类。我们用一个不精确的分类的分类的分类的分类的分类的精确的变式的分类的变式的变式的变式的变式的变制 。