Analyzing the computational complexity of evolutionary algorithms (EAs) for binary search spaces has significantly informed our understanding of EAs in general. With this paper, ...
Abstract. Evolutionary algorithms have been shown to be very successful for a wide range of NP-hard combinatorial optimization problems. We investigate the NP-hard problem of compu...
Stefan Kratsch, Per Kristian Lehre, Frank Neumann,...
Abstract. This paper presents two different efficiency-enhancement techniques for probabilistic model building genetic algorithms. The first technique proposes the use of a mutatio...
Abstract–A new evolutionary programming algorithm (NEP) using the non-uniform mutation operator instead of Gaussian or Cauchy mutation operators is proposed. NEP has the merits o...
The performance of Evolutionary Programming (EP) is affected by many factors (e.g. mutation operators and selection strategies). Although the conventional approach with Gaussian mu...
A robust dynamic evolutionary algorithm (labeled RODEA), where both the robust calculation and mutation operator are based on an orthogonal design, is proposed in this paper. Prev...
Sanyou Y. Zeng, Rui Wang, Hui Shi, Guang Chen, Hug...
We propose a novel algorithm called GA-MDP for solving the frequency assigment problem. GA-MDP inherits the spirit of genetic algorithms with an adaptation of Markov Decision Proc...
Evolution strategy (ES) and particle swarm optimization (PSO) are two of the most popular research topics for tackling real-parameter optimization problems in evolutionary computa...