Abstract Particle Swarm Optimization (PSO), in its present form, has been in existence for
roughly a decade, with formative research in related domains (such as social modelling …

This paper presents a comprehensive learning particle swarm optimization algorithm with
enhanced exploration and exploitation, named as “heterogeneous comprehensive learning …

A hierarchical version of the particle swarm optimization (PSO) metaheuristic is introduced in
this paper. In the new method called H-PSO, the particles are arranged in a dynamic …

Predicting the future for financial gain is a difficult, sometimes profitable activity. The focus of
this book is the application of biologically inspired algorithms (BIAs) to financial modelling. In …

A particle swarm optimization (PSO) based algorithm for finding the Pareto solutions of
multiobjective design problems is proposed. To enhance the global searching ability of the …

The field of natural computing has been the focus of a substantial research effort in recent
decades. One particular strand of this concerns the development of computational …

This authoritative handbook reveals the connections between bioinspired techniques and
the development of solutions to problems that arise in diverse problem domains. It provides …

This study presents an evolutionary neural fuzzy network, designed using the functional-link-
based neural fuzzy network (FLNFN) and a new evolutionary learning algorithm. This new …

Dynamic environments abound and offer particular challenges for all optimisation and
problem solving methods. A well-known strategy for survival in dynamic environments is to …

Particles in the standard particle swarm optimization (PSO) algorithms, and most of its
modifications, follow the same behaviours. That is, particles implement the same velocity …