Genetic Algorithms and Grouping Problems
Genetic Algorithms and Grouping Problems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithm and Graph Partitioning
IEEE Transactions on Computers
Spin-flip symmetry and synchronization
Evolutionary Computation
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Fitness Distance Correlation as a Measure of Problem Difficulty for Genetic Algorithms
Proceedings of the 6th International Conference on Genetic Algorithms
A New Genetic Local Search Algorithm for Graph Coloring
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A Genetic Hybrid For Critical Heat Flux Function Approximation
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Isomorphism, Normalization, And A Genetic Algorithm For Sorting Network Optimization
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Is the common good? a new perspective developed in genetic algorithms
Is the common good? a new perspective developed in genetic algorithms
Fitness Landscapes, Memetic Algorithms, and Greedy Operators for Graph Bipartitioning
Evolutionary Computation
Fitness landscape analysis and memetic algorithms for the quadratic assignment problem
IEEE Transactions on Evolutionary Computation
Effects of phenotypic redundancy in structure optimization
IEEE Transactions on Evolutionary Computation
New topologies for genetic search space
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Geometric crossover for multiway graph partitioning
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Geometric crossovers for multiway graph partitioning
Evolutionary Computation
Representations for evolutionary algorithms
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Representations for evolutionary algorithms
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Representations for evolutionary algorithms
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Genetic approaches for graph partitioning: a survey
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Representations for evolutionary algorithms
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Quotient geometric crossovers and redundant encodings
Theoretical Computer Science
Representations for evolutionary algorithms
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Representations for evolutionary algorithms
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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Normalization is an approach that transforms the genotype of one parent to be consistent with that of the other parent. It is a method for alleviating difficulties caused by redundant encodings in genetic algorithms. We show that normalization plays a role of reducing the search space to another one of less size. We provide insight into normalization through theoretical arguments, performance tests, and examination of fitness-distance correlations.