Recent advances in metaheuristics have shown the advantages of using the Lévy
distribution, which models a kind of random walk (named “Lévy flight”) with occasional “big” …

Determining the optimum type and location of new wells is an essential component in the
efficient development of oil and gas fields. The optimization problem is, however …

In this correspondence, an approach based on coevolutionary particle swarm optimization to
solve constrained optimization problems formulated as min-max problems is presented. In …

Cuckoo search optimization algorithm is a biologically inspired optimization algorithm, which
is widely used to solve many optimization problems. However, it has been empirically …

In real-world applications, there are many fields involving dynamic multi-objective
optimization problems (DMOPs), in which objectives are in conflict with each other and …

Many practical optimization problems are constrained and have a bounded search space. In
this paper, we propose and compare a wide variety of bound handling techniques for …

Optimization problems can generally be classified as continuous and discrete, based on the
nature of the solution space. A recently developed chemical-reaction-inspired metaheuristic …

The aim of this book is to present and analyse theoretical advances and also emerging
practical applications of swarm and evolutionary intelligence. It comprises nine chapters …

This paper aims at the optimal designing of a stand-alone microgrid (PV/wind/battery/diesel)
system, which can be utilized to meet the demand load requirements of a small residential …

Adaptive designs are increasingly developed and used to improve all phases of clinical
trials and in biomedical studies in various ways to address different statistical issues. We first …