Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
Designing and Building Parallel Programs: Concepts and Tools for Parallel Software Engineering
Designing and Building Parallel Programs: Concepts and Tools for Parallel Software Engineering
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
A Survey of Optimization by Building and Using Probabilistic Models
Computational Optimization and Applications
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
On Decentralizing Selection Algorithms
Proceedings of the 6th International Conference on Genetic Algorithms
Design of a Framework for Data-Intensive Wide-Area Applications
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
Takeover time curves in random and small-world structured populations
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Linkage Problem, Distribution Estimation, and Bayesian Networks
Evolutionary Computation
The virtual data grid: a new model and architecture for data-intensive collaboration
SSDBM '03 Proceedings of the 15th International Conference on Scientific and Statistical Database Management
Proceedings of the 28th international conference on Software engineering
ACM SIGEVOlution
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Validity of the single processor approach to achieving large scale computing capabilities
AFIPS '67 (Spring) Proceedings of the April 18-20, 1967, spring joint computer conference
Meandre: Semantic-Driven Data-Intensive Flows in the Clouds
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
SofEA: a pool-based framework for evolutionary algorithms using CouchDB
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Designing and testing a pool-based evolutionary algorithm
Natural Computing: an international journal
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Data-intensive computing has positioned itself as a valuable programming paradigm to efficiently approach problems requiring processing very large volumes of data. This paper presents a pilot study about how to apply the data-intensive computing paradigm to evolutionary computation algorithms. Two representative cases (selectorecombinative genetic algorithms and estimation of distribution algorithms) are presented, analyzed, and discussed. This study shows that equivalent data-intensive computing evolutionary computation algorithms can be easily developed, providing robust and scalable algorithms for the multicore-computing era. Experimental results show how such algorithms scale with the number of available cores without further modification.