Collection of experiments related to swarm intelligence
rosenbrock function optimization with four different methods (unconstrained optimization)
Comparative Study on Differential Evolution and Genetic Algorithms applied to minimization of Rastrigin and Rosenbrock Functions
A set of Jupyter notebooks that investigate and compare the performance of several numerical optimization techniques, both unconstrained (univariate search, Powell's method and Gradient Descent (fixed step and optimal step)) and constrained (Exterior Penalty method).
Particle Swarm Optimisation in the N-dimensional space
Classical optimization algorithms implemented from scratch, including steepest descent, Newton, conjugate gradient, BFGS, DFP, and L-BFGS, evaluated on Rosenbrock and MNIST logistic regression.
Minimize rosenbrock function - differential evolution.
A study of genetic algorithms and differential evolution optimization algorithms applied on the Rosenbrock function
Rosenbrock function done prallel in C.
Solutions for Labs of Nature Inspired Computing course offered at Innopolis University
MATLAB Numerical Optimization Methods
Numerical optimization algorithms in Python, including steepest descent, BFGS, Newton's method, Armijo line search, and cubic interpolation.
A pure NumPy implementation of Gradient Descent optimization, verified against Google JAX's automatic differentiation and benchmarked on the Rosenbrock function
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