Cooperative bat searching algorithm: A combined perspective from multiagent coordination and swarm intelligence
Haopeng Zhang, Qing Hui · 2017
In this paper, a multiagent coordination framework is introduced for a recently developed swarm intelligence optimization algorithm, so-called “Bat Searching Algorithm” or “Bat Algorithm” (BA). Due to a great success of cooperative multiagent coordination applications in control areas, such as consensus problems and formation control for multiagent systems, in this paper, this cooperative multiagent coordination idea is used and embedded into a swarm intelligence optimization algorithm. Specifically, a graph communication topology is introduced and a consensus protocol is used in BA to share the velocity information of the bats. This proposed Cooperative Bat Searching Algorithm or Cooperative Bat Algorithm (CBA) shows faster convergence rate compared with the original BA by solving several benchmark functions. Moreover, some modifications are also applied into the proposed CBA method to further improve its performance. Based on the numerical evaluation results, the proposed CBA can show significant performance enhancement compared with the original BA. Finally, as an application, the economic load dispatch problem is considered and numerically solved by the proposed CBA method.