Genetic algorithms are best suited for optimization problems involving large search spaces. The problem space encountered when optimizing the transmission parameters of an agile or...
Timothy R. Newman, Rakesh Rajbanshi, Alexander M. ...
Cellular genetic algorithms (cGAs) are mainly characterized by their spatially decentralized population, in which individuals can only interact with their neighbors. In this work,...
The error threshold of replication is an important notion of the quasispecies evolution model; it is a critical mutation rate (error rate) beyond which structures obtained by an e...
Abstract. This work describes the use of genetic algorithms for automating the photogrammetric network design process. When planning a photogrammetric network, the cameras should b...
The paper presents an extension of Vose’s Markov chain model for genetic algorithm (GA). The model contains not only standard genetic operators such as mutation and crossover bu...