Scilab 5.3.3
Please note that the recommended version of Scilab is 2024.1.0. This page might be outdated.
See the recommended documentation of this function
temp_law_fsa
The Szu and Hartley Fast simulated annealing
Calling Sequence
T_out = temp_law_fsa(T_in,step_mean,step_var,temp_stage,n,param)
Arguments
- T_in
the temperature at the current stage
- step_mean
the mean value of the objective function computed during the current stage
- step_var
the variance value of the objective function computed during the current stage
- temp_stage
the index of the current temperature stage
- n
the dimension of the decision variable (the x in f(x))
- param
not used for this temperature law
- T_out
the temperature for the temperature stage to come
Description
This function implements the Fast simulated annealing of Szu and Hartley.
Examples
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 FSA 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_fsa, neigh_func_fsa); printf('optimal solution:\n'); disp(x_opt); printf('value of the objective function = %f\n', f_opt); scf(); subplot(2,1,1); xtitle('Fast 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-');
See Also
- optim_sa — A Simulated Annealing optimization method
- temp_law_huang — The Huang temperature decrease law for the simulated annealing
- neigh_func_default — A SA function which computes a neighbor of a given point
Authors
- collette
Yann COLLETTE (ycollet@freesurf.fr)
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