Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Adaptive Selection Methods for Genetic Algorithms
Proceedings of the 1st International Conference on Genetic Algorithms
Scheduling Problems and Traveling Salesmen: The Genetic Edge Recombination Operator
Proceedings of the 3rd International Conference on Genetic Algorithms
Opt4J: a modular framework for meta-heuristic optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Implementation matters: programming best practices for evolutionary algorithms
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
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This article gives an overview over eaLib, a framework for the implementation of evolutionary algorithms written in Java. After an introduction the kind of genetic representation used in the toolkit is discussed and provided genetico perators are introduced. Thereafter the concept of breaking up an evolutionary algorithm into components and the definition of interfaces for these components is discussed. On that basis a controller model for flexible and fast creation of algorithms is presented. The paper concludes with a section dealing with issues of parallelization of evolutionary algorithms and gives a short outlook on future work.