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particle-swarm-optimization

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A cutting-edge implementation of Particle Swarm Optimization (PSO) tailored for navigating and optimizing complex non-convex functions. This project encapsulates an advanced algorithmic approach, leveraging swarm intelligence to efficiently converge on global minima in multimodal landscapes.

  • Updated Nov 24, 2023
  • Jupyter Notebook

this project visualizes the optimization process of benchmark functions using two Evolutionary Algorithms (EAs): Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO). It aims to provide an intuitive understanding of the algorithms' dynamics and performance in function optimization tasks

  • Updated May 11, 2024
  • Python

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