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 population-based stochastic optimization algorithm
motivated by intelligent collective behavior of some animals such as flocks of birds or …

In nature, almost every organism ages and has a limited lifespan. Aging has been explored
by biologists to be an important mechanism for maintaining diversity. In a social animal …

Particle swarm optimization (PSO) has undergone many changes since its introduction in
1995. As researchers have learned about the technique, they have derived new versions …

This paper presents a variant of particle swarm optimizers (PSOs) that we call the
comprehensive learning particle swarm optimizer (CLPSO), which uses a novel learning …

This paper introduces a novel parameter automation strategy for the particle swarm
algorithm and two further extensions to improve its performance after a predefined number …

Many areas in power systems require solving one or more nonlinear optimization problems.
While analytical methods might suffer from slow convergence and the curse of …

This is the first book devoted entirely to Particle Swarm Optimization (PSO), which is a non-
specific algorithm, similar to evolutionary algorithms, such as taboo search and ant colonies …

Particle swarm optimization is a recently invented high-performance optimizer that is very
easy to understand and implement. It is similar in some ways to genetic algorithms or …

Data clustering is one of the most popular techniques in data mining. It is a process of
partitioning an unlabeled dataset into groups, where each group contains objects which are …