In this paper, we present e cient algorithms for adjusting con guration parameters of genetic algorithms that operate in a noisy environment. Assuming that the population size is ...
Subset Feature Selection problems can have severalattributes which may make Messy Genetic Algorithms an appropriateoptimization method. First, competitive solutions may often use ...
L. Darrell Whitley, J. Ross Beveridge, Cesar Guerr...
Molecular docking software makes computational predictions of the interaction of molecules. This can be useful, for example, in evaluating the binding of candidate drug molecules ...
Christopher D. Rosin, R. Scott Halliday, William E...
In this paper we first review the main results in the theory of schemata in Genetic Programming (GP) and summarise a new GP schema theory which is based on a new definition of s...
Parallel Distributed Genetic Programming (PDGP) is a new form of Genetic Programming (GP) suitable for the development of programs with a high degree of parallelism. Programs are ...
This paper introduces the wave model, a novel approach on analyzing the behavior of GAs. Our aim is to give techniques that have practical relevance and provide tools for improvin...
A methodology is described for synthesizing signal processing networks, which are used to solve a low-cost medical signal processing problem. The approach makes use of genetic alg...
This paper presents a genetic algorithm (GA) with specialized encoding, initialization and local search genetic operators to optimize communication network topologies. This NPhard...