Three optimization problem domains are created and applied to the randomized hill climbing, simulated annealing, genetic and MIMIC randomized optimization algorithms. Also, a neural network implementation is reimplemented using randomized optimization algorithms from the mlrose_hiive Python library.
machine-learning optimization genetic-algorithm jupyter-notebook eight-queen-problem simulated-annealing hill-climbing metaheuristics georgia-tech travelling-salesman-problem mimic cs7641 randomized-optimization four-peaks-problem neural-network-training mlrose
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Sep 28, 2026 - Jupyter Notebook