PSO-SA

A hybrid optimization algorithm that combines Particle Swarm Optimization and Simulated Annealing to solve several test functions.

How it works

• Uses Simulated Annealing in each iteration of the particle swarm to enable escaping local optimum
• Uses Several test functions and outputs a solution graph

How to run

1. Choose the test function and bounds to use by uncommenting them
2. Make sure nv is aligned with the amount of variables in the problem
3. If nv > 2, make sure that activatePlot = False
4. Make sure that mm is the same as the type of problem (-1 for max, 1 for min)
5. If there is a problem with the optimal value, useOptimal can be used
6. Optimization parameters can be freely changed
7. Plot titles need to be manually changed with the chosen test function