Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
A Survey of Optimization by Building and Using Probabilistic Models
Computational Optimization and Applications
Finding Multimodal Solutions Using Restricted Tournament Selection
Proceedings of the 6th International Conference on Genetic Algorithms
From Recombination of Genes to the Estimation of Distributions I. Binary Parameters
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning
A New Genetic Algorithm for the Quadratic Assignment Problem
INFORMS Journal on Computing
Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications (Studies in Computational Intelligence)
Scalability problems of simple genetic algorithms
Evolutionary Computation
Using previous models to bias structural learning in the hierarchical BOA
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Analysis of estimation of distribution algorithms and genetic algorithms on NK landscapes
Proceedings of the 10th annual conference on Genetic and evolutionary computation
CrossNet: a framework for crossover with network-based chromosomal representations
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Intelligent bias of network structures in the hierarchical BOA
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Dependency structure matrix, genetic algorithms, and effective recombination
Evolutionary Computation
Performance of evolutionary algorithms on random decomposable problems
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
The computational complexity of N-K fitness functions
IEEE Transactions on Evolutionary Computation
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This paper describes a network crossover operator based on knowledge gathered from either prior problem-specific knowledge or linkage learning methods such as estimation of distribution algorithms (EDAs). This operator can be used in a genetic algorithm (GA) to incorporate linkage in recombination. The performance of GA with network crossover is compared to that of GA with uniform crossover and the hierarchical Bayesian optimization algorithm (hBOA) on 2D Ising spin glasses, NK landscapes, and SK spin glasses. The results are analyzed and discussed.