Genetic Algorithm (GA) is one of the most well-regarded evolutionary algorithms in the
history. This algorithm mimics Darwinian theory of survival of the fittest in nature. This …

For over 25 years, most multi-objective evolutionary algorithms (MOEAs) have adopted
selection criteria based on Pareto dominance. However, the performance of Pareto-based …

Genetic Algorithm (GA) is one of the first population-based stochastic algorithm proposed in
the history. Similar to other EAs, the main operators of GA are selection, crossover, and …

Dependence Modeling with Copulas covers the substantial advances that have taken place
in the field during the last 15 years, including vine copula modeling of high-dimensional …

Optimization is one of the research areas where quantum computing could bring significant
benefits. In this scenario, a hybrid quantum–classical variational algorithm, the Quantum …

Metaheuristics are widely recognized as efficient approaches for many hard optimization
problems. This paper provides a survey of some of the main metaheuristics. It outlines the …

There are growing demands for condition-based monitoring of gearboxes, and therefore
new methods to improve the reliability, effectiveness, accuracy of the gear fault detection …

Evolutionary algorithms (EAs) are often well-suited for optimization problems involving
several, often conflicting objectives. Since 1985, various evolutionary approaches to …

This is the second edition of our 2003 book. It is primarily a book for lecturers and graduate
and undergraduate students. To this group the book offers a thorough introduction to …

The traveling salesman problem is one of the most well-known hybrid optimization
problems. It is one of the (NP-complete) problems that its various applications have …