Evaluation of the general applicability of Dragoon for the k-center problem

TL;DR

This paper evaluates the Dragoon algorithm's effectiveness for the k-center problem, highlighting its strengths and limitations through challenging instance testing.

Contribution

It provides an empirical assessment of Dragoon's applicability and compares its performance against other methods on difficult problem instances.

Findings

Dragoon performs well on many instances.

Certain challenging instances reveal Dragoon's limitations.

The study identifies scenarios where alternative methods outperform Dragoon.

Abstract

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.