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 …

The Particle Swarm Optimisation (PSO) algorithm was inspired by the social and biological
behaviour of bird flocks searching for food sources. In this nature-based algorithm …

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 …

Multimodal optimization (MMO) aiming to locate multiple optimal (or near-optimal) solutions
in a single simulation run has practical relevance to problem solving across many fields …

This paper presents an overview of our most recent results concerning the Particle Swarm
Optimization (PSO) method. Techniques for the alleviation of local minima, and for detecting …

Multimodal optimization amounts to finding multiple global and local optima (as opposed to
a single solution) of a function, so that the user can have a better knowledge about different …

Many scientific, engineering and economic problems involve the optimisation of a set of
parameters. These problems include examples like minimising the losses in a power grid by …

Niching is an important technique for multimodal optimization. Most existing niching
methods require specification of certain niching parameters in order to perform well. These …

This paper constitutes a first study of the Particle Swarm Optimization (PSO) method in
Multiobjective Optimization (MO) problems. The ability of PSO to detect Pareto Optimal …

The performance of the Particle Swarm Optimization method in coping with Constrained
Optimization problems is investigated in this contribution. In the adopted approach a non …