Toward an extrapolation of the simulated annealing convergence theory onto the simple genetic algorithm144438
The Simple Genetic Algorithm: Foundations and Theory
The Simple Genetic Algorithm: Foundations and Theory
A New Interpretation of Schema Notation that Overtums the Binary Encoding Constraint
Proceedings of the 3rd International Conference on Genetic Algorithms
A Markov Chain Analysis on A Genetic Algorithm
Proceedings of the 5th International Conference on Genetic Algorithms
Epistasis in Genetic Algorithms: An Experimental Design Perspective
Proceedings of the 6th International Conference on Genetic Algorithms
Some experiments in machine learning using vector evaluated genetic algorithms (artificial intelligence, optimization, adaptation, pattern recognition)
Evolutionary Computation
Simple genetic algorithms with linear fitness
Evolutionary Computation
Modeling simple genetic algorithms
Evolutionary Computation
Logarithmic convergence of random heuristic search
Evolutionary Computation
Form Invariance and Implicit Parallelism
Evolutionary Computation
Structural Search Spaces and Genetic Operators
Evolutionary Computation
Extended probe method for linkage discovery over high-cardinality alphabets
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Evolutionary Computation
The simple genetic algorithm and the walsh transform: Part i, theory
Evolutionary Computation
Detecting the epistatic structure of generalized embedded landscape
Genetic Programming and Evolvable Machines
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Natural coding: a more efficient representation for evolutionary learning
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Stopping criteria for genetic algorithms with application to multiobjective optimization
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
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A complete generalization of the Vose genetic algorithm model from the binary to higher cardinality case is provided. Boolean AND and EXCLUSIVE-OR operators are replaced by multiplication and addition over rings of integers. Walsh matrices are generalized with finite Fourier transforms for higher cardinality usage. Comparison of results to the binary case are provided.