Adaptive tracking theory of molecular evolution challenges mutation neutrality

For a long time, evolutionary biologists have thought that the genetic mutations that drive the evolution of genes and ...
IEEE

A Local Knowledge Transfer-Based Evolutionary Algorithm for Constrained Multitask Optimization

Abstract: Evolutionary multitask optimization (EMTO) can solve multiple tasks simultaneously by leveraging the relevant information between tasks, but existing EMTO algorithms do not take into account ...
IEEE

A Subspace Search-Based Evolutionary Algorithm for Large-Scale Constrained Multiobjective Optimization and Application

Abstract: Large-scale constrained multiobjective optimization problems (LSCMOPs) exist widely in science and technology. LSCMOPs pose great challenges to algorithms due to the need to optimize ...
Frontiers

A dynamic multitask evolutionary algorithm for high-dimensional feature selection based on multi-indicator task construction and elite competition learning

High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...