Alternative Mutation Operators in Collaborative Neurodynamic Optimization

Xinqi LI, Jun WANG, Sam KWONG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

3 Citations (Scopus)


Collaborative neurodynamic optimization (CNO) is a global search technique that integrates the neurodynamic optimization with a swarm intelligence algorithm. Diversity is a key point for global optimization. Mutation operator is employed in CNO to ensure diversity. In the existing literature, the diversification performance of different mutation operators is unknown. In this paper, four mutation operators, Gaussian, Cauchy, Levy and wavelet mutations, are analyzed to compare the performances of mutation operators. Simulation results on four benchmark multimodal functions are discussed.
Original languageEnglish
Title of host publication10th International Conference on Information Science and Technology, ICIST 2020
Publication statusPublished - 11 Sept 2020
Externally publishedYes

Bibliographical note

This work was supported in part by the National Natural Science Foundation of China under grant 61673330 and by the Research Grants Council of the Hong Kong Special Administrative Region of China, under Grants 11208517 and 11202318, and by the Key Project of Science and Technology Innovation 2030 supported by the Ministry of Science and Technology of China (Grant No. 2018AAA0101301).


  • collaborative neurodynamic optimization
  • global optimization
  • mutation operator


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