README.md

Optimization Techniques Assignments

This repository contains three assignments completed for the course Optimization Techniques at AUTH.

The assignments focus on unconstrained and constrained optimization problems, implemented using several optimization methods.

Works Overview

Work 1: Unconstrained Optimization (Single Variable)

Minimization of a single-variable function without constraints using:

• Bisection Method
• Golden Section Method
• Fibonacci Method
• Bisection Method using Derivatives

Work 2: Unconstrained Optimization (Multiple Variables)

Minimization of a multivariable function without constraints using:

• Steepest Descent Method
• Newton’s Method
• Levenberg–Marquardt Method

Work 3: Constrained Optimization

Minimization of a two-variable function under constraints using:

• Projected Gradient Descent Method

Project: Genetic Algorithms

Function approximation using weighted Gaussian functions, with weights optimized via a Genetic Algorithm.

Structure

Each work is contained in a separate folder (Work 1, Work 2, Work 3) and includes the corresponding implementation and report.