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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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Donkey and Smuggler Optimization Algorithm || STEP-BY-STEP || ~xRay Pixy

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Donkey and Smuggler Optimization Algorithm


Learn Donkey and Smuggler Optimization Algorithm Step-By-Step with Examples
Video Chapters:
Introduction: 00:00
Donkey's Behavior: 02:02
Donkey Mode: 04:20
Donkey and Smuggler Optimization Algorithm: 06:49
Smuggler Mode: 08:02
Donkey and Smuggler Optimization Algorithm STEPS: 11:54
Donkey and Smuggler Optimization Algorithm FLOWCHART: 15:39
Conclusion: 16:24
About Donkey and Smuggler Optimization Algorithm: - Introduced in 2019 by Ahmed S Shamsaldin et. al. - Nature Inspired Population-Based Metaheuristic Optimization Algorithm. - Used to Solve Complex Optimization Problems. - Implemented to solve Real Life Optimization Problems such as Travelling Salesman Problem (TSP) Routing Problems
    Ambulance Routing

Donkey and Smuggler Optimization Algorithm MODES:
  • Smuggler Mode [Non-Adaptive]
  • Donkey Mode [Adapative]
Donkey and Smuggler Optimization Algorithm STEPS:
  1. Initialize algorithm parameters i.e., Population Size, Dimensions, and Maximum Iterations.
  2. Initialize the agent's position in the search space.
  3. Calculate Fitness values for agents.
  4. Choose the best solution among all and send the donkey.
  5. Reevaluate the vest solution's fitness value. Check if it is a better solution or not.
  6. If the Current Solution is NOT GOOD:
RUN: Re-evaluate the Population Fitness and update the best solution.
FACE and Suicide: Choose the second-best solution as the best solution.
FACE and Support: Use the second-best solution to support the best solution.


Video Chapters: Introduction: 00:00 Donkey's Behavior: 02:02 Donkey Mode: 04:20 Donkey and Smuggler Optimization Algorithm: 06:49 Smuggler Mode: 08:02 Donkey and Smuggler Optimization Algorithm STEPS: 11:54 Donkey and Smuggler Optimization Algorithm FLOWCHART: 15:39 Conclusion: 16:24

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