article · Procedia Environmental Sciences · 2011

A Genetic Algorithm Based on Combination Operators

Cited by 13Open access

Abstract

Dual operator and inverse operator are defined as two new genetic operators respectively in this paper. Then a genetic algorithm based on inverse and dual combination operator was designed to overcome the defect of genetic algorithm in local searching, which combined with uniform crossover. The genetic algorithm is proved to be convergent. Experiments show that it has better searching performance and it has good reference to string-coded genetic algorithm in solving nonlinear optimization problems.

Cite this paper

APA 7

Xun-bo, S., & Zhou, X. (2011). A Genetic Algorithm Based on Combination Operators. Procedia Environmental Sciences, 11, 346–350. https://doi.org/10.1016/j.proenv.2011.12.055

MLA 9

Xun-bo, Shuai, and Xiangguang Zhou. “A Genetic Algorithm Based on Combination Operators.” Procedia Environmental Sciences, vol. 11, 2011, pp. 346–50, https://doi.org/10.1016/j.proenv.2011.12.055.

Chicago

Xun-bo, Shuai, and Xiangguang Zhou. 2011. “A Genetic Algorithm Based on Combination Operators.” Procedia Environmental Sciences 11: 346–50. https://doi.org/10.1016/j.proenv.2011.12.055.

Harvard

Xun-bo, S. and Zhou, X. (2011) ‘A Genetic Algorithm Based on Combination Operators’, Procedia Environmental Sciences, 11, pp. 346–350. Available at: https://doi.org/10.1016/j.proenv.2011.12.055.

BibTeX

@article{xunbo2011genetic,
  title = {{A Genetic Algorithm Based on Combination Operators}},
  author = {Xun-bo, Shuai and Zhou, Xiangguang},
  journal = {Procedia Environmental Sciences},
  volume = {11},
  pages = {346--350},
  year = {2011},
  doi = {10.1016/j.proenv.2011.12.055}
}

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