From the past few decades many nature inspired algorithms have been developed and
gaining more popularity because of their effectiveness in solving problems of distinct …

Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has
gained prominence in the last two decades due to its ease of application in unsupervised …

Over the ages, nature has constantly been a rich source of inspiration for science, with much
still to discover about and learn from. Swarm Intelligence (SI), a major branch of artificial …

Metaheuristic optimization algorithms have become popular choice for solving complex and
intricate problems which are otherwise difficult to solve by traditional methods. In the present …

K-Means is a popular cluster analysis method which aims to partition a number of data
points into K clusters. It has been successfully applied to a number of problems. However …

In recent years, different optimization methods have been developed for optimization
problem. Many of these methods are inspired by swarm behaviors in nature. In this paper, a …

Recently, virtual coupling has aroused increasing interest in regard to achieving flexible and
on-demand train operations. However, one of the main challenges in increasing the …

In this paper, at first, a novel combination of Particle Swarm Optimization (PSO) and Genetic
Algorithm (GA) is introduced. This hybrid algorithm uses the operators such as mutation …

Meta-heuristic optimization algorithms have become popular choice for solving complex and
intricate problems which are otherwise difficult to solve by traditional methods. In the present …

针对粒子群优化(Particle Swarm Optimization, PSO) 算法在维度高, 特征稀疏的文本聚类过程
中, 随着算法迭代次数增加在后期陷入局部最优的问题, 提出采用多样性更好的差分进化 …