7 #define MAX2(a,b) ((a) > (b) ? (a) : (b))
8 #define MIN2(a,b) ((a) < (b) ? (a) : (b))
10 /* Table of constant values */
12 static double c_b7 = 0.;
14 /* *********************************************************************** */
15 /* SUBROUTINE PNET ALL SYSTEMS 01/09/22 */
17 /* GENERAL SUBROUTINE FOR LARGE-SCALE BOX CONSTRAINED MINIMIZATION THAT */
18 /* USE THE LIMITED MEMORY VARIABLE METRIC METHOD BASED ON THE STRANG */
22 /* II NF NUMBER OF VARIABLES. */
23 /* II NB CHOICE OF SIMPLE BOUNDS. NB=0-SIMPLE BOUNDS SUPPRESSED. */
24 /* NB>0-SIMPLE BOUNDS ACCEPTED. */
25 /* RI X(NF) VECTOR OF VARIABLES. */
26 /* II IX(NF) VECTOR CONTAINING TYPES OF BOUNDS. IX(I)=0-VARIABLE */
27 /* X(I) IS UNBOUNDED. IX(I)=1-LOVER BOUND XL(I).LE.X(I). */
28 /* IX(I)=2-UPPER BOUND X(I).LE.XU(I). IX(I)=3-TWO SIDE BOUND */
29 /* XL(I).LE.X(I).LE.XU(I). IX(I)=5-VARIABLE X(I) IS FIXED. */
30 /* RI XL(NF) VECTOR CONTAINING LOWER BOUNDS FOR VARIABLES. */
31 /* RI XU(NF) VECTOR CONTAINING UPPER BOUNDS FOR VARIABLES. */
32 /* RO GF(NF) GRADIENT OF THE OBJECTIVE FUNCTION. */
33 /* RA GN(NF) OLD GRADIENT OF THE OBJECTIVE FUNCTION. */
34 /* RO S(NF) DIRECTION VECTOR. */
35 /* RA XO(NF) ARRAY CONTAINING INCREMENTS OF VARIABLES. */
36 /* RA GO(NF) ARRAY CONTAINING INCREMENTS OF GRADIENTS. */
37 /* RA XS(NF) AUXILIARY VECTOR. */
38 /* RA GS(NF) AUXILIARY VECTOR. */
39 /* RA XM(NF*MF) ARRAY CONTAINING INCREMENTS OF VARIABLES. */
40 /* RA GM(NF*MF) ARRAY CONTAINING INCREMENTS OF GRADIENTS. */
41 /* RA U1(MF) AUXILIARY VECTOR. */
42 /* RA U2(MF) AUXILIARY VECTOR. */
43 /* RI XMAX MAXIMUM STEPSIZE. */
44 /* RI TOLX TOLERANCE FOR CHANGE OF VARIABLES. */
45 /* RI TOLF TOLERANCE FOR CHANGE OF FUNCTION VALUES. */
46 /* RI TOLB TOLERANCE FOR THE FUNCTION VALUE. */
47 /* RI TOLG TOLERANCE FOR THE GRADIENT NORM. */
48 /* RI MINF_EST ESTIMATION OF THE MINIMUM FUNCTION VALUE. */
49 /* RO GMAX MAXIMUM PARTIAL DERIVATIVE. */
50 /* RO F VALUE OF THE OBJECTIVE FUNCTION. */
51 /* II MIT MAXIMUM NUMBER OF ITERATIONS. */
52 /* II MFV MAXIMUM NUMBER OF FUNCTION EVALUATIONS. */
53 /* II MFG MAXIMUM NUMBER OF GRADIENT EVALUATIONS. */
54 /* II IEST ESTIMATION INDICATOR. IEST=0-MINIMUM IS NOT ESTIMATED. */
55 /* IEST=1-MINIMUM IS ESTIMATED BY THE VALUE MINF_EST. */
56 /* II MOS1 CHOICE OF RESTARTS AFTER A CONSTRAINT CHANGE. */
57 /* MOS1=1-RESTARTS ARE SUPPRESSED. MOS1=2-RESTARTS WITH */
58 /* STEEPEST DESCENT DIRECTIONS ARE USED. */
59 /* II MOS1 CHOICE OF DIRECTION VECTORS AFTER RESTARTS. MOS1=1-THE */
60 /* NEWTON DIRECTIONS ARE USED. MOS1=2-THE STEEPEST DESCENT */
61 /* DIRECTIONS ARE USED. */
62 /* II MOS2 CHOICE OF PRECONDITIONING STRATEGY. MOS2=1-PRECONDITIONING */
63 /* IS NOT USED. MOS2=2-PRECONDITIONING BY THE LIMITED MEMORY */
64 /* BFGS METHOD IS USED. */
65 /* II MF THE NUMBER OF LIMITED-MEMORY VARIABLE METRIC UPDATES */
66 /* IN EACH ITERATION (THEY USE 2*MF STORED VECTORS). */
67 /* IO ITERM VARIABLE THAT INDICATES THE CAUSE OF TERMINATION. */
68 /* ITERM=1-IF ABS(X-XO) WAS LESS THAN OR EQUAL TO TOLX IN */
69 /* MTESX (USUALLY TWO) SUBSEQUEBT ITERATIONS. */
70 /* ITERM=2-IF ABS(F-FO) WAS LESS THAN OR EQUAL TO TOLF IN */
71 /* MTESF (USUALLY TWO) SUBSEQUEBT ITERATIONS. */
72 /* ITERM=3-IF F IS LESS THAN OR EQUAL TO TOLB. */
73 /* ITERM=4-IF GMAX IS LESS THAN OR EQUAL TO TOLG. */
74 /* ITERM=6-IF THE TERMINATION CRITERION WAS NOT SATISFIED, */
75 /* BUT THE SOLUTION OBTAINED IS PROBABLY ACCEPTABLE. */
76 /* ITERM=11-IF NIT EXCEEDED MIT. ITERM=12-IF NFV EXCEEDED MFV. */
77 /* ITERM=13-IF NFG EXCEEDED MFG. ITERM<0-IF THE METHOD FAILED. */
79 /* VARIABLES IN COMMON /STAT/ (STATISTICS) : */
80 /* IO NRES NUMBER OF RESTARTS. */
81 /* IO NDEC NUMBER OF MATRIX DECOMPOSITION. */
82 /* IO NIN NUMBER OF INNER ITERATIONS. */
83 /* IO NIT NUMBER OF ITERATIONS. */
84 /* IO NFV NUMBER OF FUNCTION EVALUATIONS. */
85 /* IO NFG NUMBER OF GRADIENT EVALUATIONS. */
86 /* IO NFH NUMBER OF HESSIAN EVALUATIONS. */
88 /* SUBPROGRAMS USED : */
89 /* S PCBS04 ELIMINATION OF BOX CONSTRAINT VIOLATIONS. */
90 /* S PS1L01 STEPSIZE SELECTION USING LINE SEARCH. */
91 /* S PYADC0 ADDITION OF A BOX CONSTRAINT. */
92 /* S PYFUT1 TEST ON TERMINATION. */
93 /* S PYRMC0 DELETION OF A BOX CONSTRAINT. */
94 /* S PYTRCD COMPUTATION OF PROJECTED DIFFERENCES FOR THE VARIABLE METRIC */
96 /* S PYTRCG COMPUTATION OF THE PROJECTED GRADIENT. */
97 /* S PYTRCS COMPUTATION OF THE PROJECTED DIRECTION VECTOR. */
98 /* S MXDRCB BACKWARD PART OF THE STRANG FORMULA FOR PREMULTIPLICATION */
99 /* OF THE VECTOR X BY AN IMPLICIT BFGS UPDATE. */
100 /* S MXDRCF FORWARD PART OF THE STRANG FORMULA FOR PREMULTIPLICATION */
101 /* OF THE VECTOR X BY AN IMPLICIT BFGS UPDATE. */
102 /* S MXDRSU SHIFT OF COLUMNS OF THE RECTANGULAR MATRICES A AND B. */
103 /* SHIFT OF ELEMENTS OF THE VECTOR U. THESE SHIFTS ARE USED IN */
104 /* THE LIMITED MEMORY BFGS METHOD. */
105 /* S MXUDIR VECTOR AUGMENTED BY THE SCALED VECTOR. */
106 /* RF MXUDOT DOT PRODUCT OF TWO VECTORS. */
107 /* S MXVNEG COPYING OF A VECTOR WITH CHANGE OF THE SIGN. */
108 /* S MXVCOP COPYING OF A VECTOR. */
109 /* S MXVSCL SCALING OF A VECTOR. */
110 /* S MXVSET INITIATINON OF A VECTOR. */
111 /* S MXVDIF DIFFERENCE OF TWO VECTORS. */
113 /* EXTERNAL SUBROUTINES : */
114 /* SE OBJ COMPUTATION OF THE VALUE OF THE OBJECTIVE FUNCTION. */
115 /* CALLING SEQUENCE: CALL OBJ(NF,X,FF) WHERE NF IS THE NUMBER */
116 /* OF VARIABLES, X(NF) IS THE VECTOR OF VARIABLES AND FF IS */
117 /* THE VALUE OF THE OBJECTIVE FUNCTION. */
118 /* SE DOBJ COMPUTATION OF THE GRADIENT OF THE OBJECTIVE FUNCTION. */
119 /* CALLING SEQUENCE: CALL DOBJ(NF,X,GF) WHERE NF IS THE NUMBER */
120 /* OF VARIABLES, X(NF) IS THE VECTOR OF VARIABLES AND GF(NF) */
121 /* IS THE GRADIENT OF THE OBJECTIVE FUNCTION. */
122 /* -- OBJ and DOBJ are replaced by a single function, objgrad, in NLopt */
125 /* LIMITED MEMORY VARIABLE METRIC METHOD BASED ON THE STRANG */
128 static void pnet_(int *nf, int *nb, double *x, int *
129 ix, double *xl, double *xu, double *gf, double *gn,
130 double *s, double *xo, double *go, double *xs,
131 double *gs, double *xm, double *gm, double *u1,
132 double *u2, double *xmax, double *tolx, double *tolf,
133 double *tolb, double *tolg, nlopt_stopping *stop,
134 double *minf_est, double *
135 gmax, double *f, int *mit, int *mfv, int *mfg,
136 int *iest, int *mos1, int *mos2, int *mf,
137 int *iterm, stat_common *stat_1,
138 nlopt_func objgrad, void *objgrad_data)
140 /* System generated locals */
144 /* Builtin functions */
146 /* Local variables */
147 double a = 0.0, b = 0.0;
151 double fo, fp, po, pp, ro, rp;
158 double alf1, alf2, eta0, eta9, par1, par2;
159 int mes1, mes2, mes3;
160 double rho1, rho2, eps8, eps9;
161 int mred, iold, nred;
167 double rmin, rmax, umax, tolp, tols;
170 int iterd, mtesf, ntesf;
172 int iters, irest, inits, kters, maxst;
179 /* Parameter adjustments */
235 *minf_est = -HUGE_VAL; /* changed from -1e60 by SGJ */
250 *tolg = 1e-8; /* SGJ: was 1e-6, but this sometimes stops too soon */
253 /* removed by SGJ: this check prevented us from using minf_max <= 0,
254 which doesn't make sense. Instead, if you don't want to have a
255 lower limit, you should set minf_max = -HUGE_VAL */
257 *tolb = *minf_est + 1e-16;
263 /* changed by SGJ: default is no limit (INT_MAX) on # iterations/fevals */
281 kit = -(ires1 * *nf + ires2);
284 /* INITIAL OPERATIONS WITH SIMPLE BOUNDS */
288 for (i__ = 1; i__ <= i__1; ++i__) {
289 if ((ix[i__] == 3 || ix[i__] == 4) && xu[i__] <= xl[i__]) {
292 } else if (ix[i__] == 5 || ix[i__] == 6) {
299 luksan_pcbs04__(nf, &x[1], &ix[1], &xl[1], &xu[1], &eps9, &kbf);
300 luksan_pyadc0__(nf, &n, &x[1], &ix[1], &xl[1], &xu[1], &inew);
302 *f = objgrad(*nf, &x[1], &gf[1], objgrad_data);
305 if (nlopt_stop_time(stop)) { *iterm = 100; goto L11080; }
308 luksan_pytrcg__(nf, nf, &ix[1], &gf[1], &umax, gmax, &kbf, &iold);
309 luksan_mxvcop__(nf, &gf[1], &gn[1]);
310 luksan_pyfut1__(nf, f, &fo, &umax, gmax, xstop, stop, tolg,
311 &kd, &stat_1->nit, &kit, mit, &stat_1->nfg, mfg, &
312 ntesx, &mtesx, &ntesf, &mtesf, &ites, &ires1, &ires2, &irest, &
317 if (nlopt_stop_time(stop)) { *iterm = 100; goto L11080; }
319 luksan_pyrmc0__(nf, &n, &ix[1], &gn[1], &eps8, &umax, gmax, &rmax, &
321 if (umax > eps8 * *gmax) {
322 irest = MAX2(irest,1);
325 luksan_mxvcop__(nf, &x[1], &xo[1]);
328 /* DIRECTION DETERMINATION */
331 if (kit < stat_1->nit) {
343 luksan_mxvneg__(nf, &gn[1], &s[1]);
344 gnorm = sqrt(luksan_mxudot__(nf, &gn[1], &gn[1], &ix[1], &kbf));
349 rho1 = luksan_mxudot__(nf, &gn[1], &gn[1], &ix[1], &kbf);
352 d__1 = eps, d__2 = sqrt(gnorm);
353 par = MIN2(d__1,d__2);
356 d__1 = par, d__2 = 1. / (double) stat_1->nit;
357 par = MIN2(d__1,d__2);
365 luksan_mxvset__(nf, &c_b7, &s[1]);
366 luksan_mxvneg__(nf, &gn[1], &gs[1]);
367 luksan_mxvcop__(nf, &gs[1], &xs[1]);
372 b = luksan_mxudot__(nf, &xm[1], &gm[1], &ix[1], &kbf);
376 luksan_mxdrcb__(nf, &mx, &xm[1], &gm[1], &u1[1], &u2[1], &xs[1], &
378 a = luksan_mxudot__(nf, &gm[1], &gm[1], &ix[1], &kbf);
381 luksan_mxvscl__(nf, &d__1, &xs[1], &xs[1]);
383 luksan_mxdrcf__(nf, &mx, &xm[1], &gm[1], &u1[1], &u2[1], &xs[1], &
387 rho = luksan_mxudot__(nf, &gs[1], &xs[1], &ix[1], &kbf);
397 pp = sqrt(eta0 / luksan_mxudot__(nf, &xs[1], &xs[1], &ix[1], &kbf));
399 luksan_mxudir__(nf, &pp, &xs[1], &xo[1], &x[1], &ix[1], &kbf);
400 objgrad(*nf, &x[1], &gf[1], objgrad_data);
404 luksan_mxvdif__(nf, &gf[1], &gn[1], &go[1]);
407 luksan_mxvscl__(nf, &d__1, &go[1], &go[1]);
408 alf = luksan_mxudot__(nf, &xs[1], &go[1], &ix[1], &kbf);
409 if (alf <= 1. / eta9) {
410 /* IF (ALF.LE.1.0D-8*SIG) THEN */
412 /* CG FAILS (THE MATRIX IS NOT POSITIVE DEFINITE) */
415 luksan_mxvneg__(nf, &gn[1], &s[1]);
427 luksan_mxudir__(nf, &alf, &xs[1], &s[1], &s[1], &ix[1], &kbf);
429 luksan_mxudir__(nf, &d__1, &go[1], &gs[1], &gs[1], &ix[1], &kbf);
430 rho2 = luksan_mxudot__(nf, &gs[1], &gs[1], &ix[1], &kbf);
431 snorm = sqrt(luksan_mxudot__(nf, &s[1], &s[1], &ix[1], &kbf));
432 if (rho2 <= par * rho1) {
440 luksan_mxvcop__(nf, &gs[1], &go[1]);
441 luksan_mxdrcb__(nf, &mx, &xm[1], &gm[1], &u1[1], &u2[1], &go[1], &
445 luksan_mxvscl__(nf, &d__1, &go[1], &go[1]);
447 luksan_mxdrcf__(nf, &mx, &xm[1], &gm[1], &u1[1], &u2[1], &go[1], &
449 rho2 = luksan_mxudot__(nf, &gs[1], &go[1], &ix[1], &kbf);
451 luksan_mxudir__(nf, &alf, &xs[1], &go[1], &xs[1], &ix[1], &kbf);
454 luksan_mxudir__(nf, &alf, &xs[1], &gs[1], &xs[1], &ix[1], &kbf);
458 luksan_mxudir__(nf, &alf, &xs[1], &gs[1], &xs[1], &ix[1], &kbf);
461 /* SIG=RHO2+ALF*ALF*SIG */
465 /* AN INEXACT SOLUTION IS OBTAINED */
469 /* ------------------------------ */
470 /* END OF DIRECTION DETERMINATION */
471 /* ------------------------------ */
473 luksan_mxvcop__(nf, &xo[1], &x[1]);
474 luksan_mxvcop__(nf, &gn[1], &gf[1]);
476 p = luksan_mxudot__(nf, &gn[1], &s[1], &ix[1], &kbf);
482 /* TEST ON DESCENT DIRECTION */
485 irest = MAX2(irest,1);
486 } else if (p + told * gnorm * snorm <= 0.) {
490 /* UNIFORM DESCENT CRITERION */
492 irest = MAX2(irest,1);
496 /* PREPARATION OF LINE SEARCH */
499 rmin = alf1 * gnorm / snorm;
501 d__1 = alf2 * gnorm / snorm, d__2 = *xmax / snorm;
502 rmax = MIN2(d__1,d__2);
509 if (nlopt_stop_time(stop)) { *iterm = 100; goto L11080; }
513 luksan_pytrcs__(nf, &x[1], &ix[1], &xo[1], &xl[1], &xu[1], &gf[1], &go[1],
514 &s[1], &ro, &fp, &fo, f, &po, &p, &rmax, &eta9, &kbf);
519 luksan_ps1l01__(&r__, &rp, f, &fo, &fp, &p, &po, &pp, minf_est, &maxf, &rmin,
520 &rmax, &tols, &tolp, &par1, &par2, &kd, &ld, &stat_1->nit, &kit, &
521 nred, &mred, &maxst, iest, &inits, &iters, &kters, &mes,
526 luksan_mxudir__(nf, &r__, &s[1], &xo[1], &x[1], &ix[1], &kbf);
527 luksan_pcbs04__(nf, &x[1], &ix[1], &xl[1], &xu[1], &eps9, &kbf);
528 *f = objgrad(*nf, &x[1], &gf[1], objgrad_data);
532 p = luksan_mxudot__(nf, &gf[1], &s[1], &ix[1], &kbf);
539 luksan_mxvcop__(nf, &xo[1], &x[1]);
540 luksan_mxvcop__(nf, &go[1], &gf[1]);
541 irest = MAX2(irest,1);
545 luksan_pytrcd__(nf, &x[1], &ix[1], &xo[1], &gf[1], &go[1], &r__, f, &fo, &
546 p, &po, &dmax__, &kbf, &kd, &ld, &iters);
547 xstop = nlopt_stop_dx(stop, &x[1], &xo[1]);
552 luksan_mxdrsu__(nf, &mx, &xm[1], &gm[1], &u1[1]);
553 luksan_mxvcop__(nf, &xo[1], &xm[1]);
554 luksan_mxvcop__(nf, &go[1], &gm[1]);
558 luksan_pyadc0__(nf, &n, &x[1], &ix[1], &xl[1], &xu[1], &inew);
560 irest = MAX2(irest,1);
568 /* NLopt wrapper around pnet_, handling dynamic allocation etc. */
569 nlopt_result luksan_pnet(int n, nlopt_func f, void *f_data,
570 const double *lb, const double *ub, /* bounds */
571 double *x, /* in: initial guess, out: minimizer */
573 nlopt_stopping *stop,
574 int mf, /* subspace dimension (0 for default) */
575 int mos1, int mos2) /* 1 or 2 */
579 double *xl, *xu, *gf, *gn, *s, *xo, *go, *xs, *gs, *xm, *gm, *u1, *u2;
580 double gmax, minf_est;
581 double xmax = 0; /* no maximum */
582 double tolg = 0; /* default gradient tolerance */
583 int iest = 0; /* we have no estimate of min function value */
584 int mit = 0, mfg = 0; /* default no limit on #iterations */
585 int mfv = stop->maxeval;
589 ix = (int*) malloc(sizeof(int) * n);
590 if (!ix) return NLOPT_OUT_OF_MEMORY;
593 mf = MAX2(MEMAVAIL/n, 10);
594 if (stop->maxeval && stop->maxeval <= mf)
595 mf = MAX2(stop->maxeval, 1);
599 work = (double*) malloc(sizeof(double) * (n * 9 + MAX2(n,n*mf)*2 +
603 mf = 0; /* allocate minimal memory */
607 return NLOPT_OUT_OF_MEMORY;
610 xl = work; xu = xl + n;
611 gf = xu + n; gn = gf + n; s = gn + n;
612 xo = s + n; go = xo + n; xs = go + n; gs = xs + n;
613 xm = gs + n; gm = xm + MAX2(n*mf,n);
614 u1 = gm + MAX2(n*mf,n); u2 = u1 + MAX2(n,mf);
616 for (i = 0; i < n; ++i) {
617 int lbu = lb[i] <= -0.99 * HUGE_VAL; /* lb unbounded */
618 int ubu = ub[i] >= 0.99 * HUGE_VAL; /* ub unbounded */
619 ix[i] = lbu ? (ubu ? 0 : 2) : (ubu ? 1 : (lb[i] == ub[i] ? 5 : 3));
624 /* ? xo does not seem to be initialized in the
625 original Fortran code, but it is used upon
626 input to pnet if mf > 0 ... perhaps ALLOCATE initializes
627 arrays to zero by default? */
628 memset(xo, 0, sizeof(double) * MAX2(n,n*mf));
630 pnet_(&n, &nb, x, ix, xl, xu,
631 gf, gn, s, xo, go, xs, gs, xm, gm, u1, u2,
634 /* fixme: pass tol_rel and tol_abs and use NLopt check */
654 case 1: return NLOPT_XTOL_REACHED;
655 case 2: return NLOPT_FTOL_REACHED;
656 case 3: return NLOPT_MINF_MAX_REACHED;
657 case 4: return NLOPT_SUCCESS; /* gradient tolerance reached */
658 case 6: return NLOPT_SUCCESS;
659 case 12: case 13: return NLOPT_MAXEVAL_REACHED;
660 case 100: return NLOPT_MAXTIME_REACHED;
661 case -999: return NLOPT_FORCED_STOP;
662 default: return NLOPT_FAILURE;