Harris Hawks Optimization Algorithm Step-by-Step with Example ~xRay PixyππΏπ
Harris Hawks Optimization Algorithm
Harris hawks optimizer (HHO) is a swarm-based optimization method. This algorithm mimics the Exploring, Exploiting, and Attacking strategies of Harris Hawks. Harris hawk's optimization algorithm can be used to solve different engineering problems. Harris Hawk is also known as Dusky Hawk. Harris Hawk hunt in cooperative groups. Harris Hawk Diet: Large insects, Birds, Lizards, and Mammals.
Harris Hawks Optimization Algorithm Step-by-Step
INPUT: Population Size (N), and a maximum number of iterations (MaxT).
OUTPUT: Target Location and its Fitness Values.
1.) Initialize the population randomly π_π ( π=1,2,3,4,…π ).
2.) Check While ( (t ≥ MaxT )Stopping Criteria is Matched or Not )
3.) Calculate fitness value for each hawk and Select Best.
4.) Set π_ππππππ‘ as the best location of the rabbit.
5.) For each hawk Position: update Energy and Jump Strength.
6.) Exploration Phase
7.) Exploitation Phase
8.) Update Location Vector using 4 strategies: Soft Round-Up, Hard Round-Up, Soft round-up with progressive rapid dives, Hard round-up with progressive rapid dives.
9.) Return Best Rabbit Location and its Fitness Value.
Topics covered in this video:
Introduction
Harris Hawks Optimization Algorithm Introduction
About Harris Hawk
Harris Hawks Optimization Algorithm Steps.
Exploration Phase in HHO
How Harris Hawks Detect Prey?
How to update Harris Hawks Position?
How Harris Hawks Detect prey?
How Harris Hawks exploit the target?
Update Rabbit Position in HHO
Exploitation Phase in HHO.
How Haws catch the prey?
Conclusion
No comments