Evolutionary Computation Meets Machine Learning: A Survey

@article{Zhang2011EvolutionaryCM,
  title={Evolutionary Computation Meets Machine Learning: A Survey},
  author={Jun Zhang and Zhi-hui Zhan and Ying Lin and Ni Chen and Yue-jiao Gong and J. Zhong and H. Chung and Y. Li and Yu-hui Shi},
  journal={IEEE Computational Intelligence Magazine},
  year={2011},
  volume={6},
  pages={68-75}
}
  • Jun Zhang, Zhi-hui Zhan, +6 authors Yu-hui Shi
  • Published 2011
  • Computer Science
  • IEEE Computational Intelligence Magazine
  • Evolutionary computation (EC) is a kind of optimization methodology inspired by the mechanisms of biological evolution and behaviors of living organisms. In the literature, the terminology evolutionary algorithms is frequently treated the same as EC. This article focuses on making a survey of researches based on using ML techniques to enhance EC algorithms. In the framework of an ML-technique enhanced-EC algorithm (MLEC), the main idea is that the EC algorithm has stored ample data about the… CONTINUE READING
    175 Citations
    Enhancing the performance of evolutionary algorithms: A novel maturity-based adaptation strategy
    An Energy-Based Sampling Technique for Multi-Objective Restricted Boltzmann Machine
    • 6
    Adaptive genetic algorithm based on density distribution of population
    • PDF
    A survey on evolutionary machine learning
    • 35
    • PDF
    Application of on-line machine learning in optimization algorithms: A case study for local search
    • Cong Hao, T. Yoshimura
    • Computer Science
    • 2017 9th Computer Science and Electronic Engineering (CEEC)
    • 2017
    Adaptive differential evolution with optimization state estimation
    • 12

    References

    SHOWING 1-10 OF 77 REFERENCES
    A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning
    • 1,338
    • PDF
    Accelerating Differential Evolution Using an Adaptive Local Search
    • N. Noman, H. Iba
    • Mathematics, Computer Science
    • IEEE Transactions on Evolutionary Computation
    • 2008
    • 578
    • PDF
    Reducing Fitness Evaluations Using Clustering Techniques and Neural Network Ensembles
    • 165
    • PDF
    Hybridization of evolutionary algorithms and local search by means of a clustering method
    • 101
    • PDF
    Hybrid Evolutionary Search Method Based on Clusters
    • 20
    Clustering-Based Adaptive Crossover and Mutation Probabilities for Genetic Algorithms
    • 259
    • PDF
    Opposition-Based Differential Evolution
    • 1,210
    • PDF
    A Probabilistic Memetic Framework
    • 209
    • PDF
    JADE: Adaptive Differential Evolution With Optional External Archive
    • 2,024
    • PDF
    Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization
    • 2,445
    • PDF