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 …

The field of parallel metaheuristics is continuously evolving as a result of new technologies
and needs that researchers have been encountering. In the last decade, new models of …

This e-book is devoted to global optimization algorithms, which are methods to find optimal
solutions for given problems. It especially focuses on Evolutionary Computation by …

Over the last few decades, many population-based swarm and evolutionary algorithms were
introduced in the literature. It is well known that population topology or sociometry plays an …

Differential evolution is a very popular optimization algorithm and considerable research has
been devoted to the development of efficient search operators. Motivated by the different …

Research in exact algorithms, heuristics and metaheuristics for solving combinatorial
optimization problems is nowadays highly on the rise. The main advantage of using exact …

Differential evolution (DE) algorithms compose an efficient type of evolutionary algorithm
(EA) for the global optimization domain. Although it is well known that the population …

The artificial bee colony (ABC) algorithm is a metaheuristic algorithm for numerical
optimization. It is based on the intelligent foraging behavior of honey bees. This paper …

This paper provides a comprehensive review regarding the applications of particle swarm
optimization (PSO) in the railway domain. One hundred and thirty nine (139) publications in …

The Artificial Intelligence field continues to be plagued by what can only be described as
'bold promises for the future syndrome', often perpetrated by researchers who should know …