optimizationswarm intelligenceSwarm-based optimization algorithms have prevailed in the field of metaheuristics for the past decades. With their application field spanning from combinatorial problems to continuous and mixed integer problems, swarm-based algorithms are currently part of the state-of-the-art...
On the one hand, when considering the first steps in swarm-based optimization, algorithms such as Ant System [8] and Particle Swarm Optimization [9] are immediately noticed. Since they are accepted as the first methods based on swarm intelligence, it is common to reference them as landmarks...
一、背景知识(1)起源1995年,受到鸟群觅食行为的规律性启发,James Kennedy和Russell Eberhart建立了一个简化算法模型,经过多年改进最终形成了 粒子群优化算法(Particle Swarm Optimization, PSO) ,也可称为粒…
To statistically analyze the significance of our proposed method, McNemer’s test83is performed between the ALO algorithm used in this method with several other metaheuristic optimization algorithms, popularly used for feature selection. McNemer’s test is a non-parametric test, based on the null h...
In this paper, we propose a particle swarm optimization based clustering algorithm with mobile sink for wireless sensor network. In this algorithm, the virtual clustering technique is performed during routing process which makes use of the particle swarm optimization algorithm. The residual energy and ...
Zhao J, Wen T, Jahanshahi H, Cheong KH (2022) The random walk-based gravity model to identify influential nodes in complex networks. Inf Sci 609:1706–1720 Google Scholar Shi XH, Liang YC, Lee HP, Lu C, Wang Q (2007) Particle swarm optimization-based algorithms for TSP and generalize...
In this section, the basic principles of Particle Swarm Optimization (PSO) are presented and an in depth description of the algorithms that have been developed and applied for the considered cloaking problems is given. After discussing the theoretical basis of the swarm optimization method and its ...
In spite of a wide range of optimization algorithms that could be used, there is not a main one that is considered to be the best for any case. One optimization method that is suitable for a problem might not be so for another one; it depends on several features, for example, whether...
network genetic-algorithm distributed-system particle-swarm-optimization soft-computing extreme-learning-machine internet-traffic-data meta-heuristics time-series-forecasting nature-inspired-algorithms opposition-based-learning evolution-algorithm whale-optimization tug-of-war-optimization swarm-optimization-algorithm...
The results show that the PSO with mutation algorithm is significantly better than other PSO-based algorithms because it can overcome the drawback of trapping in the local optimum points and obtain better inverse solutions. The effects of measurement errors, number of dimensionalities, and number ...