Zen and the art of genetic algorithms
Proceedings of the third international conference on Genetic algorithms
ASPARAGOS An Asynchronous Parallel Genetic Optimization Strategy
Proceedings of the 3rd International Conference on Genetic Algorithms
Distributed and Persistent Evolutionary Algorithms: A Design Pattern
Proceedings of the Second European Workshop on Genetic Programming
Map-reduce-merge: simplified relational data processing on large clusters
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Peer-to-Peer Optimization in Large Unreliable Networks with Branch-and-Bound and Particle Swarms
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
A distributed pool architecture for genetic algorithms
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Linux Journal
Professional NoSQL
SofEA: a pool-based framework for evolutionary algorithms using CouchDB
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Validating design choices in a pool-based distributed evolutionary algorithms architecture
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
EvoSpace: a distributed evolutionary platform based on the tuple space model
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
Designing and testing a pool-based evolutionary algorithm
Natural Computing: an international journal
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This work presents the mapping of an evolutionary algorithm to the CouchDB object store. This mapping decouples the population from the evolutionary algorithm, and allows a distributed and asynchronous operation of clients written in different languages. In this paper we present initial tests which prove that the novel algorithm design still performs as an evolutionary algorithm and try to find out what are the main issues concerning it, what kind of speedups should we expect, and how all this affects the fundamentals of the evolutionary algorithm.