temp_law_vfsa — This function implements the Very Fast Simulated Annealing from L. Ingber
T_out = temp_law_vfsa(T_in,step_mean,step_var,temp_stage,n, param)
the temperature at the current stage
the mean value of the objective function computed during the current stage
the variance value of the objective function computed during the current stage
the index of the current temperature stage
the dimension of the decision variable (the x in f(x))
a float: the 'c' parameter of the VFSA method (0.01 by default)
the temperature for the temperature stage to come
function y = rastrigin(x)
y = x(1)^2+x(2)^2-cos(12*x(1))-cos(18*x(2));
endfunction
x0 = [-1, -1];
Proba_start = 0.8;
It_intern = 1000;
It_extern = 30;
It_Pre = 100;
printf('SA: the VFSA algorithm\n');
T0 = compute_initial_temp(x0, rastrigin, Proba_start, It_Pre, neigh_func_default);
printf('Initial temperatore T0 = %f\n', T0);
[x_opt, f_opt, sa_mean_list, sa_var_list, temp_list] = optim_sa(x0, rastrigin, It_extern, It_intern, T0, Log = %T, temp_law_vfsa, neigh_func_vfsa);
printf('optimal solution:\n'); disp(x_opt);
printf('value of the objective function = %f\n', f_opt);
scf();
subplot(2,1,1);
xtitle('VFSA simulated annealing','Iteration','Mean / Variance');
t = 1:length(sa_mean_list);
plot(t,sa_mean_list,'r',t,sa_var_list,'g');
legend(['Mean','Variance']);
subplot(2,1,2);
xtitle('Temperature evolution','Iteration','Temperature');
plot(t,temp_list,'k-');