Heuristic Optimization Algorithm of Black-Winged Kite Fused with Osprey and Its Engineering Application

Area of Science:

• Computational Intelligence
• Swarm Intelligence
• Optimization Algorithms

Background:

• Multi-objective optimization problems present challenges due to their high-dimensional goal spaces.
• Existing swarm intelligence methods, like the Black-Winged Kite Algorithm (BKA), struggle with balancing global exploration and local exploitation, often leading to premature convergence.
• Enhancing the optimization capabilities of swarm intelligence algorithms is crucial for solving complex real-world problems.

Purpose of the Study:

• To propose an enhanced swarm intelligence optimization algorithm, the Osprey-fused Chaotic Black-Winged Kite Algorithm (OCBKA).
• To improve the global search and local development capabilities of the Black-Winged Kite Algorithm (BKA).
• To address the limitations of existing algorithms in handling high-dimensional multi-objective optimization problems.

Main Methods:

• Initialization of the population using logistic chaotic mapping for better diversity.
• Fusion of the Osprey optimization algorithm with the Black-Winged Kite Algorithm (BKA) to enhance search performance.
• Performance evaluation using CEC2005 and CEC2021 benchmark functions and three engineering optimization problems.

Main Results:

• The proposed OCBKA demonstrates a significant improvement in balancing global search and local development.
• Numerical comparisons show OCBKA's superior performance against other swarm intelligence methods on benchmark functions.
• The algorithm effectively solves complex engineering optimization problems with high accuracy and rapid convergence.

Conclusions:

• The Osprey-fused Chaotic Black-Winged Kite Algorithm (OCBKA) is a competitive and effective optimization strategy.
• OCBKA offers enhanced search capabilities, addressing the limitations of the original BKA.
• The algorithm shows strong potential for application in complex engineering optimization tasks requiring high convergence accuracy and speed.