Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
Global Optimization by Means of Distributed Evolution Strategies
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
Spatially Structured Evolutionary Algorithms: Artificial Evolution in Space and Time (Natural Computing Series)
Parallel Metaheuristics: A New Class of Algorithms
Parallel Metaheuristics: A New Class of Algorithms
Parallel Evolutionary Computations (Studies in Computational Intelligence)
Parallel Evolutionary Computations (Studies in Computational Intelligence)
pCMALib: a parallel fortran 90 library for the evolution strategy with covariance matrix adaptation
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Scaling Genetic Algorithms Using MapReduce
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
MapReduce in the Clouds for Science
CLOUDCOM '10 Proceedings of the 2010 IEEE Second International Conference on Cloud Computing Technology and Science
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We develop and evaluate a cloud scale distributed covariance matrix adaptation based evolutionary strategy for problems with dimensions as high as 400. We adopt an island based distribution model and rely on a peer-to-peer communication protocol. We identify a variety of parameters in a distributed island model that could be randomized leading to a new dynamic migration protocol that can prove advantageous when computing on the cloud. Our approach enables efficient and high quality distributed sampling while mitigating the latencies and failure risks associated with running on a cloud. We evaluate performance on a real world problem from the domain of wind energy: wind farm turbine layout optimization.