Whale Optimization Algorithm (WOA): A Nature-Inspired Metaheuristic for Single-Objective Optimization Problems
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Resource Overview
Whale Optimization Algorithm (WOA) is a novel metaheuristic optimization technique designed for solving optimization problems. The algorithm employs three core operators to simulate humpback whales' predatory behaviors: encircling prey, bubble-net feeding, and hunting mechanisms. It is specifically tailored for single-objective optimization tasks. The copyright belongs to the original developers, to whom we extend our respect. Key implementations include mathematical modeling of whale movement patterns and position updates using logarithmic spiral equations.
Detailed Documentation
The Whale Optimization Algorithm (WOA) is a relatively new metaheuristic optimization technique applied to various optimization problems. This algorithm mimics three distinct hunting behaviors of humpback whales: prey encircling, bubble-net feeding strategies, and coordinated hunting movements to solve single-objective optimization challenges. The original creators hold the intellectual property rights for this innovative approach, and we honor their contribution. WOA provides a unique solution framework by emulating whale foraging behavior through mathematical models that include:
1. Encircling mechanism using shrinking circles around the best solution
2. Spiral updating position via logarithmic spiral trajectory calculations
3. Random search phase for global exploration
Implementation typically involves iterative position updates with parameters controlling exploration-exploitation balance. Deep understanding and proper application of this algorithm can yield superior results across diverse optimization scenarios when coded with appropriate boundary handling and convergence criteria.
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