Accelerating Differential Evolution Using an Adaptive Local Search

@article{Noman2008AcceleratingDE,
  title={Accelerating Differential Evolution Using an Adaptive Local Search},
  author={Nasimul Noman and Hitoshi Iba},
  journal={IEEE Transactions on Evolutionary Computation},
  year={2008},
  volume={12},
  pages={107-125}
}
We propose a crossover-based adaptive local search (LS) operation for enhancing the performance of standard differential evolution (DE) algorithm. Incorporating LS heuristics is often very useful in designing an effective evolutionary algorithm for global optimization. However, determining a single LS length that can serve for a wide range of problems is a critical issue. We present a LS technique to solve this problem by adaptively adjusting the length of the search, using a hill-climbing… CONTINUE READING
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Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization

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