— Deceptive problems are a class of challenging problems for conventional genetic algorithms (GAs), which usually mislead the search to some local optima rather than the global o...
Yang Chen, Jinglu Hu, Kotaro Hirasawa, Songnian Yu
Abstract. In this work we have implemented and analyzed the performance of a new real coded steady-state genetic algorithm (SSGA) for the flexible ligand-receptor docking problem....
Augmenting an evolutionary algorithm with knowledge of its target problem can yield a more effective algorithm, as this presentation illustrates. The Quadratic Knapsack Problem e...
This contribution proposes an enhanced and generic selection model for Genetic Algorithms (GAs) and Genetic Programming (GP) which is able to preserve the alleles which are part o...
Michael Affenzeller, Stefan Wagner 0002, Stephan M...
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...