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Poplar Optimization Algorithm || Step-By-Step || ~xRay Pixy

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The Poplar Optimization Algorithm (POA) is a nature-inspired optimization method based on how poplar trees reproduce. It uses sexual propagation (seed dispersal by wind) for exploration and asexual reproduction (cutting and regrowth) for exploitation. Mutation and chaos factors help maintain diversity and prevent premature convergence, making POA efficient for solving complex optimization problems. Learn the Poplar Optimization Algorithm Step-By-Step using Examples. Video Chapters: Poplar Optimization Algorithm (POA) 00:00 Introduction 02:12 POA Applications 03:32 POA Steps 05:50 Execute Algorithm 1 13:45 Execute Algorithm 2 16:38 Execute Algorithm 3 18:15 Conclusion Main Points of the Poplar Optimization Algorithm (POA) Nature-Inspired Algorithm ā€“ Based on the reproductive mechanisms of poplar trees. Two Key Processes : Sexual Propagation (Seed Dispersal) ā€“ Uses wind to spread seeds, allowing broad exploration. Asexual Reproduction (Cuttings) ā€“ Strong branches grow ...
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Firefly Algorithm Step-by-Step with Numerical Example [PART - 2]

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Firefly Algorithm


Firefly algorithm is a swarm-based metaheuristic algorithm that was introduced by Yang. Firefly algorithm is used for solving optimization problems. In this video, you will learn the Firefly algorithm with an example.
Firefly Algorithm is inspired by the FLASHING Behavior of Fireflies.
For simplicity certain Assumptions used in Firefly Optimization Algorithm: -
1.) Fireflies are attracted to each other. 2) Attractiveness is proportional to BRIGHTNESS. 3.) Less Brighter Firefly is attracted to the Brighter Firefly. 4.) Attractiveness decrease as the distance between 2 fireflies increase. 5.) If the brightness for both is the same, fireflies move randomly. 6.) New Solutions are generated by Random walks & the Attraction of fireflies.

Firefly Optimization Algorithm Steps:
Initialize Parameters
Initialize Population randomly in the search space.
Compute Fitness values and select the best solution.
Check Stopping Criteria.
While Current Iteration = 1:Maximum Iteration for i=1:Population Size for j=1:Population Size If ( Light Intensity(j) < Light Intensity(i) Move Firefly i towards j. Else Move i Randomly. End If Update New Position and Light Intensity. end end Check new solutions are within bound or not. Merge Population Sort Population Rank Fireflies according to their light intensity Find Best Solution Ever Found Damp Mutation Ratio end

#Metaheuristic #Algorithms
Meta-heuristic Algorithms
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