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Repository for the evolutionary computing course at UFMG in 2020/1. Mainly topics include Combinatorial Optimization, Genetic Algorithms (GA), Differential Evolution (DE), and Particle Swarm Optimization (PSO).

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Evolutionary Computing

Repository for the evolutionary computing course at UFMG in 2020/1. Mainly topics include Combinatorial Optimization, Genetic Algorithms (GA), Differential Evolution (DE), and Particle Swarm Optimization (PSO).

These are all the projects implemented in Python Notebooks step-by-step:

  1. N-queens problem: an introduction into genetic algorithm concepts using the classical n-queens problem.

  2. Solving a Knapsack problem using a GA with a roulette wheel to rank solutions.

  3. Using a GA to start at a random string and gets to the Hamlet sentence 'Methinks it is like a weasel'. The classical Weasel Program.

  4. Using the Differential Evolution method to solve the non-convex and multimodal function rastrigin and peaks function.

  5. Implementing a Particle Swarm Optimization (PSO) method and applying it to the rastrigin and peaks function.

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Repository for the evolutionary computing course at UFMG in 2020/1. Mainly topics include Combinatorial Optimization, Genetic Algorithms (GA), Differential Evolution (DE), and Particle Swarm Optimization (PSO).

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