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- #
- #NMSMAX [x, fmax, nf] = NMSMAX(fun, x0, STOPIT, SAVIT) attempts to
- # maximize the function specified by the string fun, using the
- # starting vector x0. The Nelder-Mead direct search method is used.
- # Output arguments:
- # x = vector yielding largest function value found,
- # fmax = function value at x,
- # nf = number of function evaluations.
- # The iteration is terminated when either
- # - the relative size of the simplex is <= STOPIT(1)
- # (default 1e-3),
- # - STOPIT(2) function evaluations have been performed
- # (default inf, i.e., no limit), or
- # - a function value equals or exceeds STOPIT(3)
- # (default inf, i.e., no test on function values).
- # The form of the initial simplex is determined by STOPIT(4):
- # STOPIT(4) = 0: regular simplex (sides of equal length, the default)
- # STOPIT(4) = 1: right-angled simplex.
- # Progress of the iteration is not shown if STOPIT(5) = 0 (default 1).
- # If a non-empty fourth parameter string SAVIT is present, then
- # `SAVE SAVIT x fmax nf' is executed after each inner iteration.
- # NB: x0 can be a matrix. In the output argument, in SAVIT saves,
- # and in function calls, x has the same shape as x0.
-
- # References:
- # J.E. Dennis, Jr., and D.J. Woods, Optimization on microcomputers:
- # The Nelder-Mead simplex algorithm, in New Computing Environments:
- # Microcomputers in Large-Scale Computing, A. Wouk, ed., Society for
- # Industrial and Applied Mathematics, Philadelphia, 1987, pp. 116-122.
- # N.J. Higham, Optimization by direct search in matrix computations,
- # Numerical Analysis Report No. 197, University of Manchester, UK, 1991;
- # to appear in SIAM J. Matrix Anal. Appl, 14 (2), April 1993.
-
- # This is a heavily modified version of FMINS.M supplied with 386-MATLAB
- # version 3.5j.
-
- # By Nick Higham, Department of Mathematics, University of Manchester, UK.
- # na.nhigham@na-net.ornl.gov
- # July 27, 1991.
-
- # Translated to RLaB, Ian Searle
- # Feburary 1994.
-
- nmsmax = function (fun, X, stopit, savit)
- {
- global (eps)
-
- x = X; # Copy the input
- n = prod(size(x));
- x0 = x[:]; # Work with column vector internally.
-
- # Set up convergence parameters etc.
- if (!exist (stopit)) { stopit[1] = 1e-3; }
- tol = stopit[1]; # Tolerance for cgce test based on relative size of simplex.
- if (max(size(stopit)) == 1) { stopit[2] = inf(); } # Max no. of f-evaluations.
- if (max(size(stopit)) == 2) { stopit[3] = inf(); } # Default target for f-values.
- if (max(size(stopit)) == 3) { stopit[4] = 0; } # Default initial simplex.
- if (max(size(stopit)) == 4) { stopit[5] = 1; } # Default: show progress.
- trace = stopit[5];
- if (!exist (savit)) { savit = []; } # File name for snapshots.
-
- V = [zeros(n,1), eye(n,n)];
- f = zeros(n+1,1);
- V[;1] = x0;
- x = reshape (x0, x.nr, x.nc);
- f[1] = fun (x);
- fmax_old = f[1];
-
- if (trace) { printf("f(x0) = %9.4e\n", f[1]); }
-
- k = 0; m = 0;
-
- # Set up initial simplex.
- scale = max([norm(x0,"i"),1]);
- if (stopit[4] == 0)
- {
- # Regular simplex - all edges have same length.
- # Generated from construction given in reference [18, pp. 80-81] of [1].
- alpha = scale / (n*sqrt(2)) * [ sqrt(n+1)-1+n, sqrt(n+1)-1 ];
- V[;2:n+1] = (x0 + alpha[2]*ones(n,1)) * ones(1,n);
- for (j in 2:n+1)
- {
- V[j-1;j] = x0[j-1] + alpha[1];
- x = reshape (V[;j], x.nr, x.nc);
- f[j] = fun (x);
- }
- else
- # Right-angled simplex based on co-ordinate axes.
- alpha = scale*ones(n+1,1);
- for (j in 2:n+1)
- {
- V[;j] = x0 + alpha[j]*V[;j];
- x = reshape (V[;j], x.nr, x.nc);
- f[j] = fun (x);
- }
- }
- nf = n+1;
- how = "initial ";
-
- temp = sort (f).val;
- j = sort (f).ind;
- j = j[n+1:1:-1];
- f = f[j];
- V = V[;j];
-
- alpha = 1; beta = 1/2; gamma = 2;
-
- while (1) ###### Outer (and only) loop.
- {
- k = k+1;
-
- fmax = f[1];
- if (fmax > fmax_old)
- {
- if (!isempty(savit))
- {
- x = reshape (V[;1], x.nr, x.nc);
- write("savit", x, fmax, nf);
- }
- if (trace)
- {
- printf("Iter. %2.0f"', k);
- printf(" how = %s ", how);
- printf("nf = %3.0f, f = %9.4e (%2.1f)\n", nf, fmax, ...
- 100*(fmax-fmax_old)/(abs(fmax_old)+eps));
- }
- }
- fmax_old = fmax;
-
- ### Three stopping tests from MDSMAX.M
-
- # Stopping Test 1 - f reached target value?
- if (fmax >= stopit[3])
- {
- msg = "Exceeded target...quitting\n";
- break # Quit.
- }
-
- # Stopping Test 2 - too many f-evals?
- if (nf >= stopit[3])
- {
- msg = "Max no. of function evaluations exceeded...quitting\n";
- break # Quit.
- }
-
- # Stopping Test 3 - converged? This is test (4.3) in [1].
- v1 = V[;1];
- size_simplex = norm(V[;2:n+1]-v1[;ones(1,n)],"1") / max([1, norm(v1,"1")]);
- if (size_simplex <= tol)
- {
- sprintf(msg, "Simplex size %9.4e <= %9.4e...quitting\n", ...
- size_simplex, tol);
- break # Quit.
- }
-
- # One step of the Nelder-Mead simplex algorithm
- # NJH: Altered function calls and changed CNT to NF.
- # Changed each `fr < f(1)' type test to `>' for maximization
- # and re-ordered function values after sort.
-
- vbar = (sum(V[;1:n]')/n)'; # Mean value
- vr = (1 + alpha)*vbar - alpha*V[;n+1];
- x = reshape (vr, x.nr, x.nc);
- fr = fun (x);
- nf = nf + 1;
- vk = vr; fk = fr; how = "reflect, ";
- if (fr > f[n])
- {
- if (fr > f[1])
- {
- ve = gamma*vr + (1-gamma)*vbar;
- x = reshape (ve, x.nr, x.nc);
- fe = fun (x);
- nf = nf + 1;
- if (fe > f[1])
- {
- vk = ve; fk = fe;
- how = "expand, ";
- }
- }
- else
- vt = V[;n+1];
- ft = f[n+1];
- if (fr > ft)
- {
- vt = vr;
- ft = fr;
- }
- vc = beta*vt + (1-beta)*vbar;
- x = reshape (vc, x.nr, x.nc);
- fc = fun (x);
- nf = nf + 1;
- if (fc > f[n])
- {
- vk = vc; fk = fc;
- how = "contract,";
- else
- for (j in 2:n)
- {
- V[;j] = (V[;1] + V[;j])/2;
- x = reshape (V[;j], x.nr, x.nc);
- f[j] = fun (x);
- }
- nf = nf + n-1;
- vk = (V[;1] + V[;n+1])/2;
- x = reshape (vk, x.nr, x.nc);
- fk = fun (x);
- nf = nf + 1;
- how = "shrink, ";
- }
- }
- V[;n+1] = vk;
- f[n+1] = fk;
- temp = sort(f).val;
- j = sort (f).ind;
- j = j[n+1:1:-1];
- f = f[j];
- V = V[;j];
-
- } ###### End of outer (and only) loop.
-
- # Finished.
- if (trace) { printf(msg); }
- x = reshape (V[;1], x.nr, x.nc);
-
- return <<x = x; fmax = fmax; nf = nf>>;
- };
-