An important goal of the theory of genetic algorithms is to build predictive models of how well genetic algorithms are expected to perform, given a representation, a fitness lands...
We have proposed a method of machine translation, which acquires translation rules from translation examples using inductive learning, and have evaluated the method. And we have c...
This paper presents a genetic algorithm for the restrictive channel routing problem. The major difference of the algorithm from already known genetic algorithms for this problem c...
Vladimir N. Davidenko, Victor M. Kureichik, Victor...
We proposed a method of machine translation using inductive learning with genetic algorithms, and confirmed the effectiveness of applying genetic algorithms. However, the system b...
In a standard genetic algorithm (GA), individuals reproduce asexually: any two organisms may be parents in crossover. Gender separation and sexual selection here inspire a model o...
We are trying to piece together the knowledge of evolution with the help of biology, informatics and physics to create complex evolutionary algorithms with parallel and hierarchic...
This paper presents one target of the Evo-business project (2003-2005, conducted at University of Luxembourg) which aims at applying evolutionary algorithms (and more precisely lo...
This paper analyses the performance of a genetic algorithm using a new concept, namely a fractional-order dynamic fitness function, for the synthesis of combinational logic circuit...
In this paper we report new results concerning use of genetic algorithms in conformational analysis, field of pharmacy related to discovery and design of new drugs. The goal is to ...
Aleksander Wawer, Franciszek Seredynski, Pascal Bo...
In this article, a real-coded genetic algorithm (GA) is proposed capable of simultaneously optimizing the structure of a system (number of inputs, membership functions and rules) ...