Optimization Algorithms

Implementation of various optimization algorithms, for different test cases. More specifically:

• Find the minimum of -strictly- convex functions [1-D]
  • Bisection Method [Algorithm]
  • Golden Section Method [Algorithm]
  • Fibonacci Method [Algorithm]
  • Bisection Method (using derivative) [Algorithm]
• Find the minimum of a function with no analytic formula given [2-D]
  • Steepest Descent [Algorithm]
  • Newton [Algorithm]
  • Levenberg - Marquardt [Algorithm]
  • Conjugate Gradient (Polak–Ribière) [Algorithm]
  • quasi Newton (Davidon–Fletcher–Powell formula) [Algorithm]
• Find the minimum of a function with constraints [2-D]
  • Steepest Descent, with and without constraints [Algorithm]
• Genetic Algorithm: Approaching an unknown continuous function [2-D]