Laurent Dumas


All these programs are tested on the same example, the Rastrigin function with n
parameters on an hypercube.
With minor changes, they can be used for any real function.

1. Deterministic methods:

  A steepest descent method with a backtracking linesearch: steepest.sci

  A BFGS method with a backtracking linesearch: BFGS.sci

  The Nelder Mead method: NelderMead.sci

  The Multi Direction Search algorithm: MDS.sci

2. Stochastic methods:

  A basic simulated annealing: SA.sci

  A basic real valued genetic algorithm: GA.sci

  A basic evolution strategy: ES.sci

  An ES with cumulative search adaptation: ES-CSA.sci  , CSAES.m (idem en Matlab)


  A basic PSO algorithm: PSO.sci


  A non-dominated sorted GA (without sharing): NSGA.sci

3. Hybrid method (stochastic+deterministic):

An adaptive Hybrid method with an ES core : AHM-ES.sci

An adaptive Hybrid method with a GA core : AHM-GA.sci

4. Surrogate model (stochastic+approximated evaluations):

A surrogate model with a GA core:  AGA.sci

5. Reference:
my HDR dissertation