Bat Genetic Algorithms In Matlab

Introduction—

MATLABSolutions demonstrate In this task we are going to design the Nature-inspired algorithms have become a very promising alternative for solving very hard optimization problems in sciences and engineering. In the last two decades, many natureinspired algorithms have been developed. The inspirations for developing such nature-inspired algorithms often come from biological, chemical and physical processes in nature. In addition, some algorithms were developed by drawing characteristics that based on sociology, history or even sports. A brief review and taxonomy were proposed in the paper by Fister et al. According to the current literature, some popular nature-inspired algorithms are as follows.

THE BRIEF HISTORY OF THE BAT ALGORITHM

Since the appearance of the original paper on the bat algorithm, the literature started to expand with a wide range of applications. The original paper outlined the main formulation of the algorithm and applied the bat algorithm to study function optimization with promising results. In fact, studies indicated that BA can perform better than genetic algorithms and particle swarm optimization.

There are many new variants of the bat algorithm in the recent literature. In this brief paper, we summarize some the latest variants in Table I. For example, Mallikarjuna et al. proposed a binary bat algorithm for solving the wellknown economic load dispatch problem with the valve-point effect, and they concluded that their binary bat algorithm has many advantages.