Monarch butterfly optimization algorithm for localization in wireless sensor networks

In this paper we adjusted recent monarch butterfly optimization algorithm for solving NP-hard wireless sensor networks optimization problem, as one of the most important challenges in this area. The main goal of node localization problem is to find geographical coordinates of each sensor node with unknown position that are randomly deployed in the monitoring area. Monarch butterfly optimization is novel swarm intelligence approach and it was not tested on this or similar problems before. We adjusted basic implementation of the monarch butterfly optimization method and tested it on several problem instances that are found in the literature. We also performed a comparative analysis with other swarm intelligence metaheuristics that were tested on the same problem instances. By examining results of empirical experiments and by comparative analysis of the results from other approaches, we established that butterfly optimization algorithm can be successfully applied to wireless sensor networks optimization problem.