Quantum-inspired evolutionary algorithms (QIEAs), as a subset of evolutionary computation, are based on the principles of quantum computing such as quantum bits and quantum superp...
This paper empirically investigates parallel competent genetic algorithms (cGAs) [4]. cGAs, such as BOA [21], LINCGA [15], D5 -GA [28], can solve GA-difficult problems by automati...
In order to solve nonstationary optimization problems efficiently, evolutionary algorithms need sufficient diversity to adapt to environmental changes. The dual-population genetic...
Hereditary Repulsion (HR) is a selection method coupled with a fitness constraint that substantially improves the performance and consistency of evolutionary algorithms. This als...
Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...