Abstract The No Free Lunch Theorem states that, averaged over all optimisation problems,
all non-resampling optimisation algorithms perform equally well. In order to explain the …

In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …

Abstract Chimp Optimization Algorithm (ChoA) is a recently developed meta-heuristic
approach which is inspired by the individual intelligence and sexual motivation of chimps. It …

Biogeography is the study of the geographical distribution of biological organisms.
Mathematical equations that govern the distribution of organisms were first discovered and …

In the last decade, we observe an increasing number of nature-inspired optimization
algorithms, with authors often claiming their novelty and their capabilities of acting as …

Abstract Population size of Differential Evolution (DE) algorithms is often specified by user
and remains fixed during run. During the first decade since the introduction of DE the …

Memetic Algorithms (MAs) are computational intelligence structures combining multiple and
various operators in order to address optimization problems. The combination and …

The evaluation of artificial intelligence systems and components is crucial for the progress of
the discipline. In this paper we describe and critically assess the different ways AI systems …

This paper tackles the issue of objective performance evaluation of machine learning
classifiers, and the impact of the choice of test instances. Given that statistical properties or …

This paper tackles the difficult but important task of objective algorithm performance
assessment for optimization. Rather than reporting average performance of algorithms …