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...
This work presents a new approach to solve the location management problem by using the location areas approach. A combination of a genetic algorithm and the Hopfield neural netwo...
One of the main reasons for using parallel evolutionary algorithms (PEAs) is to obtain efficient algorithms with an execution time much lower than that of their sequential counter...
Formula One motor racing is a rich sport that spends millions on research and development of highly optimized cars. Here we describe the use of a genetic algorithm to optimize 66 s...
Genetic algorithms (GAs) are stochastic search methods that have been successfully applied in many search, optimization, and machine learning problems. Their parallel counterpart (...