Project February 2018
Optimization Algorithms
MATLAB implementations of local, constrained, and global optimization methods.
Project details
I implemented optimization methods in MATLAB, from one-dimensional searches to methods for multivariable and constrained problems. The repository groups them by the type of objective:
1-D Convex Functions:
- Bisection Method (Algorithm)
- Golden Section Method (Algorithm)
- Fibonacci Method (Algorithm)
- Bisection with Derivatives (Algorithm)
2-D Functions (no analytical form):
- Steepest Descent (Algorithm)
- Newton Method (Algorithm)
- Levenberg-Marquardt (Algorithm)
- Conjugate Gradient (Polak-Ribière) (Algorithm)
- Quasi-Newton (Davidon-Fletcher-Powell) (Algorithm)
2-D with Constraints:
- Steepest Descent with/without constraints (Algorithm)
Global Optimization:
- Genetic Algorithm for unknown continuous functions
The surface shown above illustrates how an optimization path moves across an objective function toward a minimum.