Nature inspired methods and their industry applications—Swarm intelligence algorithms
A Slowik, H Kwasnicka - IEEE Transactions on Industrial …, 2017 - ieeexplore.ieee.org
IEEE Transactions on Industrial Informatics, 2017•ieeexplore.ieee.org
In this paper, we present the swarm intelligence (SI) concept and mention some
metaheuristics belonging to the SI. We present the particle swarm optimization (PSO)
algorithm and the ant colony optimization (ACO) method as the representatives of the SI
approach. In recent years, researchers are eager to develop and apply a variety of these two
methods, despite the development of many other newer methods as Bat or FireFly
algorithms. Presenting the PSO and ACO we put their pseudocode, their properties, and …
metaheuristics belonging to the SI. We present the particle swarm optimization (PSO)
algorithm and the ant colony optimization (ACO) method as the representatives of the SI
approach. In recent years, researchers are eager to develop and apply a variety of these two
methods, despite the development of many other newer methods as Bat or FireFly
algorithms. Presenting the PSO and ACO we put their pseudocode, their properties, and …
In this paper, we present the swarm intelligence (SI) concept and mention some metaheuristics belonging to the SI. We present the particle swarm optimization (PSO) algorithm and the ant colony optimization (ACO) method as the representatives of the SI approach. In recent years, researchers are eager to develop and apply a variety of these two methods, despite the development of many other newer methods as Bat or FireFly algorithms. Presenting the PSO and ACO we put their pseudocode, their properties, and intuition lying behind them. Next, we focus on their real-life applications, indicating many papers presented varieties of basic algorithms and the areas of their applications.
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