This review paper closely explores the techniques and significances of the most potent
artificial intelligence (AI) approaches in a concise and integrated way, specifically in the …

Abstract Machine learning and optimisation are two growing fields of artificial intelligence
with an enormous number of computer science applications. The techniques in the former …

Evolutionary computation (EC) is a kind of optimization methodology inspired by the
mechanisms of biological evolution and behaviors of living organisms. In the literature, the …

Evolutionary computation has become an important problem solving methodology among
many researchers. The population-based collective learning process, selfadaptation, and …

Global optimization is a long-lasting research topic in the field of optimization, posting many
challenging theoretic and computational issues. This paper presents a novel collective …

Classification with imbalanced datasets supposes a new challenge for researches in the
framework of machine learning. This problem appears when the number of patterns that …

This paper proposes a multiclassification algorithm using multilayer perceptron neural
network models. It tries to boost two conflicting main objectives of multiclassifiers: a high …

In recent years, the historical data during the search process of evolutionary algorithms has
received increasing attention from many researchers, and some hybrid evolutionary …

For evolutionary algorithms, the search data during evolution has attracted considerable
attention and many kinds of data mining methods have been proposed to derive useful …

Evolutionary Algorithms (EAs) has attracted significantly attention with respect to complexity
scheduling problems, which is referred to evolutionary scheduling. However, EAs differ in …