set exp dies ist bla /1*100/ quantities /dZ1,dZ2,Z1,Z2/; variables dZ1_mod, dZ2_mod, dZ3_mod, P1, P2, w; table meas(exp,quantities) dZ1 dZ2 Z1 Z2 1 0.96072529 3.035614311 0.794058111 0.043613994 2 -2.25750678 3.750078555 0.954783938 0.085236982 3 -4.920342022 4.297876254 0.939846341 0.080896911 4 -6.767471248 4.682439599 0.783108452 0.161660073 5 -7.690142229 4.872038775 0.902802722 0.148670199 6 -7.279950426 4.767179402 0.515903036 0.297893574 7 -5.526570255 4.377453892 0.553194309 0.335972418 8 -3.140488492 3.96971439 0.258455116 0.324729151 9 -1.345175513 3.642174702 0.704128274 0.319232787 10 -0.619430139 3.225384432 0.486320264 0.383542309 11 -0.550141717 2.511361522 0.54775141 0.526544568 12 -1.212832852 1.69024993 0.659606521 0.536653104 13 -2.03819642 1.2379053 0.527388352 0.40512714 14 -2.44102395 1.196051151 0.452858404 0.481639455 15 -2.413025326 1.381035977 0.39222115 0.376628993 16 -2.248169378 1.461349147 0.427738353 0.543859327 17 -2.1615644 1.201891187 0.478964215 0.597210073 18 -1.912423828 0.900657105 0.283278382 0.632336052 19 -1.610478416 1.034185121 0.381451348 0.381758161 20 -1.569934465 1.427389722 0.425437635 0.620450359 21 -1.499808876 1.812044703 0.250497357 0.47629466 22 -1.45233358 2.10245599 0.377419819 0.542862013 23 -1.541057819 1.897813709 0.359889141 0.691537823 24 -1.399743655 1.281499148 0.248043478 0.643001437 25 -1.004223006 0.512601792 0.200284923 0.595235483 26 -0.78671483 -0.486826677 0.296124722 0.698787788 27 -0.941616123 -1.666849192 0.301129761 0.836202607 28 -1.256236468 -2.281393133 0.27513384 0.557130868 29 -1.522897666 -1.890326004 0.270341914 0.468745788 30 -1.553413058 -0.955350573 0.170365465 0.496704724 31 -1.418089895 -0.006356617 0.237015908 0.528474453 32 -1.196333834 0.644700379 0.178462997 0.567361093 33 -0.842159042 0.884361668 0.170474704 0.734572824 34 -0.457527574 1.138053559 0.125825686 0.385481493 35 -0.267645922 1.277428986 0.211992151 0.694982943 36 -0.320074482 1.001903892 0.171069718 0.561885533 37 -0.48442572 0.432424179 0.188779499 0.813548959 38 -0.686426528 -0.034699136 0.194749255 0.553601205 39 -0.735650465 -0.051498883 0.109903607 0.669506398 40 -0.66759301 0.328019629 0.152725821 0.543345425 41 -0.612723188 1.020154283 0.128395495 0.577512106 42 -0.590896961 1.664667639 0.144837552 0.633481654 43 -0.605928435 2.09459465 0.142281799 0.636993893 44 -0.571928181 2.217083229 0.128978865 0.596586195 45 -0.415876163 1.723268416 0.088160912 0.815423337 46 -0.212814915 0.681197562 0.097720346 0.736819026 47 -0.116877522 -0.543299866 0.100405998 0.907681013 48 -0.223435985 -1.365204807 0.148023552 0.623475173 49 -0.44332097 -1.487739564 0.107462808 0.798267855 50 -0.645697787 -0.848649423 0.120182328 0.380323377 51 -0.764799381 0.015303368 0.084554217 0.736406504 52 -0.769700437 0.440390439 0.077419772 0.698623218 53 -0.724952457 0.647927681 0.079314621 0.598991416 54 -0.660046302 0.455462106 0.060110837 0.734050505 55 -0.613800807 -0.253943815 0.079801319 0.753839859 56 -0.576998746 -1.188936659 0.058892116 0.769888322 57 -0.501567662 -1.94312295 0.041952817 0.687882678 58 -0.430047498 -2.229156624 0.064606059 0.706961021 59 -0.350012648 -1.831184684 0.03592039 0.542897551 60 -0.239675677 -0.81844157 0.031423229 0.487150463 61 -0.167331256 0.225918086 0.050091627 0.586805209 62 -0.134809206 0.885066891 0.036483264 0.639104267 63 -0.113879632 1.153953097 0.035049364 0.728599067 64 -0.118176027 1.374642725 0.039446026 0.512005731 65 -0.142364016 1.472906045 0.034987293 0.544946476 66 -0.172342137 0.789905872 0.035244881 0.956863228 67 -0.198015105 -0.174987195 0.03700028 0.521588609 68 -0.189902177 -1.028796754 0.02557958 0.81873468 69 -0.137995654 -1.753213945 0.023979284 0.700169907 70 -0.064013167 -1.779540746 0.017522927 0.517936874 71 -0.007602198 -1.282581344 0.026491132 0.566306922 72 0.005473071 -0.714838674 0.030964657 0.549561755 73 -0.002555504 -0.371166006 0.022349116 0.623852208 74 -0.023283114 -0.345668147 0.027213583 0.719922979 75 -0.060325887 -0.237168585 0.026070397 0.377271083 76 -0.102068904 -0.310057741 0.026815478 0.781891892 77 -0.133455943 -0.642591225 0.025502092 0.638046864 78 -0.133869513 -0.571050576 0.017461424 0.487567497 79 -0.105513675 -0.216130181 0.015962771 0.529535763 80 -0.073999338 0.029270118 0.018502012 0.571035788 81 -0.053504871 0.016149321 0.015113263 0.565931905 82 -0.055308554 -0.303302481 0.021398624 0.6570517 83 -0.076148635 -0.736993268 0.02012531 0.639889782 84 -0.090837983 -0.87041794 0.015289035 0.483515446 85 -0.089486193 -0.732477376 0.013052864 0.503009126 86 -0.079921678 -0.686208432 0.014963177 0.587114769 87 -0.064418692 -0.766487187 0.011219154 0.519761745 88 -0.045533345 -0.923003242 0.011977729 0.617465574 89 -0.031117501 -0.978581215 0.010446673 0.430211394 90 -0.027896739 -0.954495843 0.011352255 0.540947508 91 -0.041880412 -1.031071954 0.01296299 0.518189046 92 -0.067675828 -1.091378092 0.011555456 0.620741531 93 -0.095564071 -0.740774529 0.011760682 0.351729366 94 -0.114687359 0.010296284 0.007439442 0.476974888 95 -0.121278208 0.789475058 0.008973041 0.477655895 96 -0.112889332 1.573337298 0.006619308 0.248965963 97 -0.080846475 1.657799814 0.008441882 0.579892958 98 -0.011170906 0.557241496 0.007942511 0.718165262 99 0.124077527 -1.055601585 0.0089325 0.434447416 100 0.341515666 -2.71085172 0.008231046 0.477329155 ; equations E1, E2, obj; E1(exp).. dZ1_mod(exp) =E= -P1*meas(exp, 'Z1') ; E2(exp).. dZ2_mod(exp) =E= P1*meas(exp, 'Z1') - P2*meas(exp, 'Z2'); Obj.. w =E= sum( exp, (dZ1_mod(exp) - meas(exp, 'dZ1'))*(dZ1_mod(exp) - meas(exp, 'dZ1')) + (dZ2_mod(exp) - meas(exp, 'dZ2'))*(dZ2_mod(exp) - meas(exp, 'dZ2')) ); P1.lo = 0; P1.up = 10; P2.lo = 0; P2.up = 10; MODEL TEST / E1, E2, obj / ; OPTION LIMROW = 0.0; OPTION LIMCOL = 0.0; *OPTION MINLP=SBB; SOLVE TEST USING NLP minimiZING w;