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DOI：
10.1007/s00453-019-00565-w
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发表时间：
2014
期刊：
影响因子：
1.1
通讯作者：
Michele Scquizzato
中科院分区：
文献类型：
--
作者：
A. Antoniadis;Neal Barcelo;Michael Nugent;K. Pruhs;Michele Scquizzato
在线匹配涉及将在线请求流匹配到给定的服务器集合，所有服务器都在真实的线路中，目标是最小化匹配的服务器-请求对之间的距离之和。最佳先前已知的最佳确定性竞争比的上限和下限是线性的请求的数量，和常数，分别。我们表明，在线匹配线上基本上是等同于一个特定的搜索问题，我们称之为k-丢失的牛。然后，我们得到了第一个确定性的次线性竞争算法的在线匹配上的一行给出这样一个算法的k-丢失的奶牛问题。
Online matching on a line involves matching an online stream of requests to a given set of servers, all in the real line, with the objective of minimizing the sum of the distances between matched server-request pairs. The best previously known upper and lower bounds on the optimal deterministic competitive ratio are linear in the number of requests, and constant, respectively. We show that online matching on a line is essentially equivalent to a particular search problem, which we call k-lost-cows. We then obtain the first deterministic sub-linearly competitive algorithm for online matching on a line by giving such an algorithm for the k-lost-cows problem.