What Makes a Problem Hard for a Genetic Algorithm? Some Anomalous Results and Their Explanation
Machine Learning - Special issue on genetic algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Distributed Genetic Algorithms
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Dynamic Representations and Escaping Local Optima: Improving Genetic Algorithms and Local Search
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Nonbinary Transforms for Genetic Algorithm Problems
Selected Papers from AISB Workshop on Evolutionary Computing
Genetic algorithms as function optimizers
Genetic algorithms as function optimizers
Gene Expression and Fast Construction of Distributed Evolutionary Representation
Evolutionary Computation
Properties of Gray and Binary Representations
Evolutionary Computation
Representation, search and genetic algorithms
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Gray, binary and real valued encodings: quad search and locality proofs
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
A mixed neural-genetic algorithm for the broadcast scheduling problem
IEEE Transactions on Wireless Communications
Fitness sharing and niching methods revisited
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A gradual neural-network approach for frequency assignment in satellite communication systems
IEEE Transactions on Neural Networks
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This paper discusses new results about the effect of linear transformations (LTs) over the representation, the spectrum and the performance of standard genetic algorithms (GAs). Unitary LTs are used to set the basic outcomes and, although they can be used for theoretic GA-hard problems, their applicability is shown to be quite limited. Nevertheless, the redundancy of problems can be exploited by means of non-unitary LTs. We also propose an heuristic for construction of non-unitary LTs. Several experiments are performed in order to discuss the theoretical results of the paper.