论文标题
评估龙龙在k-center问题上的一般适用性
Evaluation of the general applicability of Dragoon for the k-center problem
论文作者
论文摘要
K-Center问题是我们在考虑复杂的服务系统时经常遇到的一个基本问题。典型的挑战包括将仓库放置在物流中或用于内容输送网络的服务器的位置。我们以前曾提出Dragoon作为一种有效的算法来解决K-Center问题。本文与其他技术相比，本文评估了龙龙，重点是潜在的最坏情况。我们使用一种进化算法来生成K-Center问题的实例，而K-Center问题对于Dragoon来说尤其具有挑战性。最终，我们的实验证实了龙龙的先前良好结果，但是，我们还可以可靠地找到方案，而其他方法显然表现明显优于其他方法。
The k-center problem is a fundamental problem we often face when considering complex service systems. Typical challenges include the placement of warehouses in logistics or positioning of servers for content delivery networks. We previously have proposed Dragoon as an effective algorithm to approach the k-center problem. This paper evaluates Dragoon with a focus on potential worst case behavior in comparison to other techniques. We use an evolutionary algorithm to generate instances of the k-center problem that are especially challenging for Dragoon. Ultimately, our experiments confirm the previous good results of Dragoon, however, we also can reliably find scenarios where it is clearly outperformed by other approaches.
