Abstract. Many real-world optimization problems have several, usually conflicting objectives. Evolutionary multi-objective optimization usually solves this predicament by searchin...
Abstract. The problem of parallel and distributed function optimization with coevolutionary algorithms is considered. Two coevolutionary algorithms are used for this purpose and co...
Franciszek Seredynski, Albert Y. Zomaya, Pascal Bo...
—Recent advances in DNA sequencing techniques have led to an unprecedented accumulation and availability of molecular sequence data that needs to be analyzed. This data explosion...
Evolutionary Algorithms, including Genetic Programming (GP), are frequently employed to solve difficult real-life problems, which can require up to days or months of computation. ...
This paper presents the integration between a co-operative co-evolutionary genetic algorithm (CCGA) and four evolutionary multiobjective optimisation algorithms (EMOAs): a multi-ob...