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An innovative complex-valued encoding black-winged kite algorithm for global optimization
Chengtao Du1, Jinzhong Zhang2, Jie Fang1
1School of Electrical and Photoelectronic Engineering, West Anhui University, Lu'an, 237012, China.
Scientific Reports
|January 6, 2025
Summary
The complex-valued black-winged kite algorithm (CBKA) enhances swarm intelligence for global optimization. It improves efficiency, precision, and convergence speed compared to the original BKA.
Area of Science:
- Computational Intelligence
- Swarm Intelligence
- Optimization Algorithms
Background:
- The standard black-winged kite algorithm (BKA) has limitations in resolution efficiency and precision.
- Existing BKA struggles with stagnation and limited exploration capabilities.
Purpose of the Study:
- To introduce an innovative complex-valued encoding BKA (CBKA) for superior global optimization.
- To enhance the computational efficacy and discovery intensity of swarm intelligence methods.
Main Methods:
- Developed CBKA by integrating complex-valued encoding with dual-diploid configuration into the BKA framework.
- Utilized inherent parallelism for separate renewal of real and imaginary parts, enhancing population diversity and exploration.
- Incorporated localized exploitation and universal exploration strategies to prevent premature convergence.
Main Results:
- CBKA demonstrated superior computational accomplishment and convergence productivity over comparative algorithms.
- The enhanced algorithm showed improved resolution precision and faster convergence efficiency.
- CBKA exhibited noteworthy stabilization and resilience in complex problem-solving.
Conclusions:
- CBKA offers significant advantages in flexibility, compatibility, and solution refinement.
- The complex-valued encoding approach effectively addresses the limitations of the original BKA.
- CBKA is a robust and efficient method for global optimization tasks, including engineering applications.
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