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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 – Based on the reproductive mechanisms of poplar trees. Two Key Processes : Sexual Propagation (Seed Dispersal) – Uses wind to spread seeds, allowing broad exploration. Asexual Reproduction (Cuttings) – Strong branches grow ...
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Manta Ray Foraging Optimization (MRFO) Algorithm Example

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Manta Ray Foraging Optimization (MRFO) Algorithm  Manta Ray Foraging Optimization (MRFO) Algorithm Example Step 01: Initialize Population Size Suppose, Population Size = 4; Lower Bound = -10; Upper Bound = 10; Maximum Iteration = 4; Suppose Initial Population  1.1  2  0.9  3 Step 02: Compute Fitness Value for each using fitness function. Fitness Values 1.21 4 0.81 9 Step 03: Obtain Best Solution Best solution = Minimum Fitness Value in the current population Best Solution = 0.81 Step 04: Check Stopping Criteria While (Current < Maximum Iteration)  1 < 4   ((True) move to next step )  If stopping criteria is then stop and return the best cost. Step 05: Update Position for each individual. For i = 1 to PopulationSize For i = 1:4 If (rand < 0.5)  THEN Cyclone Foraging Else Chain Foraging End if Step 06: Compute Fitnee Value for Each individual and Select Best Individual. Step 07: Perform Somersault Foraging.  Step 08: Co...
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