AATHA Optimization Algorithm

sphere function is tested

The AATHA Optimization Algorithm (AOA) is a recent optimization algorithm inspired by the collective behavior of birds in flight, specifically by the Attraction, Avoidance, Thrust, and Hovering mechanisms. These four principles are used to simulate the movement of birds in the search space to find the optimal solution.

• Attraction (A): This mechanism helps guide individuals towards the best solution found by the swarm.
• Avoidance (A): This allows individuals to avoid areas where they may have encountered poor solutions.
• Thrust (T): A dynamic force that propels individuals in search of better solutions.
• Hovering (H): A mechanism that helps balance the exploration and exploitation by enabling the particles to hover around potential solutions.

Key Steps in AATHA:

1. Initialization: Initialize a population of candidate solutions.
2. Attraction: Each candidate is attracted towards the best solution found in the population.
3. Avoidance: Move away from poor solutions or areas that lead to poor fitness.
4. Thrust: Dynamically apply a thrust force to move the candidate solutions further towards the global best.
5. Hovering: Introduce a hovering behavior that helps prevent premature convergence.

This algorithm is often used for continuous and discrete optimization problems, including machine learning, engineering design, and other fields where optimization is necessary.