A parallel hybrid genetic algorithm for protein structure prediction on the computational grid
Future Generation Computer Systems
Designing cellular networks using a parallel hybrid metaheuristic on the computational grid
Computer Communications
Framework for distributed evolutionary algorithms in computational grids
ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
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In this paper, we present ParadisEO-CMW, an extension of the open source ParadisEO framework, originally intended to the design and deployment of parallel hybrid meta heuristics on dedicated clusters of SMPs. Coupled with the Condor-MW library, it enables the execution of such parallel applications on volatile heterogeneous computational resources. The motivations, architecture and main features will be discussed. The framework has been tested by tackling a real-world NP-hard problem: feature selection in near-infrared spectroscopic data mining. It has been resolved by deploying a multi-level parallel model of evolutionary algorithms. Experimentations have been carried out on more than one hundred PCs originally intended for education. The obtained results are convincing, both in terms of flexibility and easiness at implementation, and in terms of efficiency and quality of provided solutions at execution.