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DNA Double-Helix and SQP Hybrid Genetic Algorithm

In: DNA Computing Based Genetic Algorithm

Author

Listed:
  • Jili Tao

    (NingboTech University, School of Information Science and Engineering)

  • Ridong Zhang

    (Hangzhou Dianzi University, The Belt and Road Information Research Institute)

  • Yong Zhu

    (NingboTech University, School of Information Science and Engineering)

Abstract

By utilizing the global exploration of GA and local exploitation characteristics of sequential quadratic programming (SQP), a hybrid genetic algorithm (HGA) is proposed in this chapter for the highly nonlinear constrained functions. Thereafter, the theoretical analysis for the convergence of the HGA is then made. In the global exploration phase, the Hamming cliff problem is solved by DNA double-helix structure, and DNA computing inspired operators are introduced to improve the global searching capability of GA.

Suggested Citation

  • Jili Tao & Ridong Zhang & Yong Zhu, 2020. "DNA Double-Helix and SQP Hybrid Genetic Algorithm," Springer Books, in: DNA Computing Based Genetic Algorithm, chapter 0, pages 57-79, Springer.
    • Handle: RePEc:spr:sprchp:978-981-15-5403-2_3
    DOI: 10.1007/978-981-15-5403-2_3
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