In recent years, Contention Resolution Schemes (CRSs), introduced by Chekuri, Vondr\'{a}k, and Zenklusen, have emerged as a general framework for obtaining feasible solutions to combinatorial optimization problems with constraints. The idea is to first solve a continuous relaxation and then round the fractional solution. When one does not have any control on the order of rounding, Online Contention Resolution Schemes (OCRSs) can be used instead, and have been successfully applied in settings such as prophet inequalities and stochastic probing. Intuitively, a greedy OCRS has to decide which elements to include in the integral solution before the online process starts. In this work, we give a simple $1/e$ - selectable greedy single item OCRS, and then proceed to show that it is optimal.
翻译:近年来,由Chekuri、Vondr\'{a}k和Zenklusen提出的内容解析计划(CRSs)已成为获得对有限制的组合优化问题的可行解决方案的一般框架。 其理念是首先解决连续放松,然后绕过分解解决方案。 当人们无法控制四舍五入的顺序时, 可以使用在线内容解析计划(OCRSs), 并且已经成功地应用于先知不平等和随机研究等环境。 直觉看来, 贪婪的OCRS必须在在线进程开始之前决定将哪些要素纳入整体解决方案。 在此工作中, 我们给出一个简单的 $/ e$ - 可选择的贪婪单项OCRS, 然后继续显示它是最佳的 。