This paper addresses two classes of different, yet interrelated optimization problems. The first class of problems involves a mobile searcher that must locate a hidden target in an environment that consists of a set of unbounded, concurrent rays. The second class pertains to the design of interruptible algorithms by means of a schedule of contract algorithms. Both types of problems capture fundamental aspects of resource allocation under uncertainty. We study several variants of these families of problems, such as searching and scheduling with probabilistic considerations, redundancy and fault-tolerance issues, randomized strategies, and trade-offs between performance and preemptions. For many of these problems, we present the first known results that apply to multi-ray and multi-problem domains. Our objective is to demonstrate that several well-motivated settings can be addressed using the same underlying approach.

本文解决了两类不同但相互关联的优化问题。第一类问题涉及移动搜索器，它必须在由一组无限的并发射线组成的环境中定位隐藏目标。第二类涉及通过合约算法的时间表设计可中断算法。这两种类型的问题都捕获了不确定性下资源分配的基本方面。我们研究了这些问题系列的几种变体，例如考虑概率的搜索和调度、冗余和容错问题、随机策略以及性能和抢占之间的权衡。对于其中许多问题，我们提出了适用于多射线和多问题域的第一个已知结果。