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City New York / Atlanta / Troy / Nagoya / / Company Neural Networks / Quantum / Computer Sciences / Future Generation Computer Systems / U.C. Berkeley Space Sciences Laboratory / Mead / Ed. CSREA Press CSREA Press / John Wiley & Sons / / Country Japan / United States / United Kingdom / / Currency pence / / Event Product Issues / / Facility University of Reading / Rensselaer Polytechnic Institute / U.C. Berkeley Space Sciences Laboratory / Dudley Observatory / University of California / / IndustryTerm live distributed systems / local and global search capability / grid computing systems / heterogeneous and faulty computing environments / metabolic systems / hybrid genetic algorithm / simulated computing environment / simulated computing hosts / simulated computing environments / distributed computing environments / continuous search spaces / search population / evolutionary programming algorithm / asynchronous evolutionary algorithms / distributed computing platforms / simulated computing environment types / multidimensional search space / parallel particle swarm optimization algorithm / heterogeneous computing environments / search spaces / faulty computing hosts / evolutionary algorithm / distributed computing / parallel genetic algorithms / simplex search / parallel computing hosts / Internet-like environments / hierarchical parallel genetic algorithms / evolutionary algorithms / simulated internet-like environment / parallel genetic algorithm / volunteer computing project2 / sequential distributed computing strategies / milky way galaxy using volunteer computing / improved genetic algorithm / larger computing systems / search methods / particle swarm algorithm / search parameters / volunteer computing project1 / adaptive particle swarm optimization algorithm / massive scale computing / large and heterogeneous computing environments / genetic algorithm / optimization algorithms / Internet-like / Internet computing / distributed computing systems / asynchronous hybrid genetic-simplex search / genetic algorithms / volunteer computing systems / hybrid algorithm / grid computing / computing / simulated homogeneous and heterogeneous computing environments / slowest computing host / asynchronous parallel genetic algorithms / distributed evolutionary algorithms / mutation operator / search space / homogeneous computing nodes / genetic search / found solutions / using parallel genetic algorithm / / NaturalFeature Island EAs / / Organization National Science Foundation / University of California / Berkeley / University of Reading / Computational Intelligence / Department of Computer Sciences / Congress / Department of Physics / Applied Physics and Astronomy / World Congress / Rensselaer Polytechnic Institute / / Person Heidi Newberg / Boleslaw K. Szymanski / Carlos A. Varela / Distributed Evolutionary Algorithms Travis Desell / David P. Anderson / David Glogau / P. Prasada / V / N. G. Pavlidis / V / Malik Magdon-Ismail / / Position initial worker / author / / Product Sony Ericsson P1i Smartphone / computing environments / computing hosts / / ProvinceOrState New York / California / Georgia / / PublishedMedium IEEE Transactions on Evolutionary Computation / / Technology bioinformatics / distributed evolutionary algorithms / evolutionary algorithm / particle swarm algorithm / peer-to-peer / genetic algorithm / hierarchical parallel genetic algorithms / Microwave / evolutionary programming algorithm / parallel particle swarm optimization algorithm / distributed processors / operating systems / hybrid genetic algorithm / adaptive particle swarm optimization algorithm / using parallel genetic algorithm / asynchronous evolutionary algorithms / optimization algorithms / CPU processors / parallel genetic algorithms / asynchronous parallel genetic algorithms / simulation / recombination / evolutionary algorithms / improved genetic algorithm / / URL http / SocialTag 
An Analysis of Massively Distributed Evolutionary Algorithms Travis Desell, David P. Anderson, Malik Magdon-Ismail, Heidi Newberg, Boleslaw K. Szymanski and Carlos A. Varela Abstract— Computational science is placing n