Abstract
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 language | English |
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| Title of host publication | 10th International Conference on Information Science and Technology (ICIST2020) |
| Publisher | IEEE |
| Pages | 126-133 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781728155586 |
| ISBN (Print) | 9781728155593 |
| DOIs | |
| Publication status | Published - 11 Sept 2020 |
| Externally published | Yes |
| Event | 10th International Conference on Information Science and Technology, ICIST 2020 - Virtual, London, United Kingdom Duration: 9 Sept 2020 → 15 Sept 2020 https://conference.cs.cityu.edu.hk/icist/ICIST2020/index.html |
Conference
| Conference | 10th International Conference on Information Science and Technology, ICIST 2020 |
|---|---|
| Country/Territory | United Kingdom |
| City | London |
| Period | 9/09/20 → 15/09/20 |
| Internet address |
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).Keywords
- collaborative neurodynamic optimization
- global optimization
- mutation operator