# Metaheuristics

# Hill climbing optimization in matlab

# A random search method[1] for the optimization of a function of n variables. in matlab

# Simulated Annealing Matlab Code

**Simulated annealing (SA)** is a generic probabilistic metaheuristic for the global optimization problem of locating a good approximation to the global optimum of a given function in a large search space. It is often used when the search space is discrete (e.g., all tours that visit a given set of cities).

# Descent gradient 1d deconvolution in matlab

# Genetic algorithm code with/without islands and simulated annealing in matlab

# Simulated annealing optimization m-file in matlab

# Simulated annealing algorithm for finding periodic orbits in matlab

# Simple example of simulated annealing optimization in matlab

# Simulated annealing for constrained optimization in matlab

# Simulated annealing optimization in matlab

# General simulated annealing algorithm in matlab

# Particle Swarm Optimization Matlab Code

Particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO optimizes a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the search-space according to simple mathematical formulae over the particle's position and velocity.