Evolutionary computation (EC) incorporates evolutionary ideas into algorithms. These algorithms can be applied to problems of biological interest. They are interesting models for evolution, so that EC ...

Genetic algorithms borrow their name and principles from biological evolution, but can they help researchers discover the fundamentals of life? Evolution is one of the most widely known theories in ...

A professor recently developed an evolutionary computation approach that offers researchers the flexibility to search for models that can best explain experimental data derived from many types of ...

Designed for courses on Evolutionary Multi-objective Optimization and Evolutionary Algorithms. This textbook is the second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, ...

Evolutionary Algorithms are a family of optimisation algorithms inspired by the process of natural selection. They are used to solve complex optimisation problems in various fields, such as ...

This course will guide students on their own intellectual journey in evolutionary computation. Early lectures provide a jumping off point — an overview of genetic algorithms, evolutionary strategies, ...

Immigration is generally considered an option in genetic algorithms, but I have found immigration to be extremely useful in almost all situations where I use evolutionary optimization. The idea of ...

It turns out that 155 years after Charles Darwin first published “On the Origin of Species,” vexing questions remain about key aspects of evolution, such as how sexual recombination and natural ...