Genetic algorithms (GAs) are stochastic search methods that have been successfully applied in many search, optimization, and machine learning problems. Their parallel counterpart (...
In this paper, we design genetic algorithm and simulated annealing algorithm and their parallel versions to solve the Closest String problem. Our implementation and experiments sho...
Abstract. A new approach to develop parallel and distributed scheduling algorithms for multiprocessor systems is proposed. Its main innovation lies in evolving a decomposition of t...
Franciszek Seredynski, Jacek Koronacki, Cezary Z. ...
This paper presents an architecture which is suitable for a massive parallelization of the compact genetic algorithm. The approach is scalable, has low synchronization costs, and i...
We introduce a new method to estimate the Java object activity in a distributed context of irregular applications. This method uses an observation mechanism which is itself a part...