The overall goal of this project is to review and practise evolutionary computation technologies for optimization, computer vision and machine learning. Specifically, the following ideas, methods and ...

This repository provides implementations for the paper: Z. He, G. G. Yen, and Z. Yi, "Robust Multiobjective Optimization via Evolutionary Algorithms," in IEEE ...

Abstract: Evolutionary multitask optimization (EMTO) is a newly emerging research area in the field of evolutionary computation. It investigates how to solve multiple optimization problems (tasks) at ...

A quantum evolutionary algorithm can be termed as a concept which utilizes certain tools of quantum computing for search and optimization purposes. A quantum algorithm relies heavily on qubits and ...

This motivates researchers to think about optimization and to apply nature-inspired algorithms, such as evolutionary algorithms (EAs) to solve optimization problems. Although these algorithms look ...

Dr. James McCaffrey of Microsoft Research says that when quantum computing becomes generally available, evolutionary algorithms for training huge neural networks could become a very important and ...

Evolutionary intelligent algorithms and machine learning methods have shown merits in dealing with complex optimization problems. Therefore, this issue aims to provide a platform for such forum to ...