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 -8.040867854 4.234650057 0.870946365 0.048687113 2 -5.48815966 4.190761021 0.85933678 0.078539866 3 -3.528178379 4.113447188 0.745430836 0.130443432 4 -2.260649734 3.982889755 0.769357954 0.174917338 5 -1.810763838 3.85469206 0.813029532 0.217291838 6 -1.972252743 3.827783623 0.857239216 0.209014477 7 -2.167815384 3.749801537 0.624951986 0.2918964 8 -2.25627915 3.458096504 0.693472615 0.364306113 9 -2.450661374 3.258440977 0.67100782 0.290362842 10 -2.696177399 3.04579219 0.669859709 0.38923466 11 -2.863505028 2.482469192 0.649649518 0.452150118 12 -2.729062559 1.820908731 0.488131212 0.438694597 13 -2.437351531 1.314224029 0.525266119 0.47125813 14 -2.339374459 1.112292204 0.557718944 0.443811175 15 -2.437865786 1.236549823 0.49813116 0.476419542 16 -2.676456071 1.603199874 0.512246519 0.445868272 17 -2.988188397 1.992495954 0.479418542 0.513980806 18 -3.203768232 2.215931566 0.501863687 0.506260592 19 -3.010535729 2.206901306 0.2854117 0.51406697 20 -2.480999581 1.6473036 0.355665443 0.645135357 21 -1.94334985 0.777522742 0.338077878 0.569080888 22 -1.426511124 -0.028549428 0.285472416 0.624057141 23 -1.051413974 -0.61024472 0.300119826 0.619808609 24 -0.96564041 -0.514612368 0.344014591 0.545226134 25 -1.081170468 0.312727255 0.288189081 0.499088758 26 -1.286791974 1.273170318 0.298694734 0.533821286 27 -1.540263288 1.663276558 0.301606627 0.647582363 28 -1.684542878 1.502132479 0.239425101 0.617329903 29 -1.647478941 1.109956076 0.224947968 0.690905491 30 -1.485016903 0.888117417 0.193728675 0.622541112 31 -1.292089628 1.136316302 0.206348334 0.565366976 32 -1.131804211 1.316163436 0.187453325 0.661647592 33 -1.010016458 0.985214578 0.187824099 0.731127338 34 -0.920563764 0.517307696 0.178547582 0.678932187 35 -0.82427612 0.274803417 0.161102204 0.651321684 36 -0.706812302 0.094123681 0.146363242 0.637479426 37 -0.600451267 -0.461192453 0.151283559 0.751461261 38 -0.525118211 -1.252149145 0.149772576 0.728950094 39 -0.455658867 -1.552874887 0.129518572 0.639773924 40 -0.400274533 -1.148254673 0.140089412 0.578707272 41 -0.36910691 -0.526306535 0.126868727 0.607572906 42 -0.356773817 -0.232784469 0.119256065 0.690523781 43 -0.397535738 -0.099557136 0.127097141 0.59460524 44 -0.503961963 -0.003603677 0.13634956 0.640756716 45 -0.614995174 -0.097659587 0.114329194 0.657145745 46 -0.677819917 -0.168744371 0.106699936 0.619989276 47 -0.691342992 -0.113270585 0.095412864 0.620700283 48 -0.671067754 -0.021504922 0.091894455 0.645144723 49 -0.63610312 0.174076788 0.091310423 0.621676199 50 -0.578799714 0.547008266 0.077545512 0.567564652 51 -0.496901528 0.698392115 0.066427215 0.701118819 52 -0.42779747 0.62972422 0.077460242 0.590510545 53 -0.380285236 0.398554003 0.065691789 0.714456336 54 -0.340440891 0.069740454 0.069850611 0.622299664 55 -0.294684636 -0.152324165 0.058617556 0.621535022 56 -0.230679761 -0.610986408 0.053187266 0.720657645 57 -0.168236097 -1.058592119 0.049725693 0.651171296 58 -0.140093332 -1.005711561 0.056569559 0.605707502 59 -0.159291323 -0.515134585 0.062569703 0.57559459 60 -0.192964366 0.020972766 0.050785232 0.591517697 61 -0.216127868 0.186960436 0.049682836 0.644783045 62 -0.230762985 -0.028021906 0.045699079 0.668310272 63 -0.241579454 -0.20503331 0.043841387 0.615110021 64 -0.257325228 -0.094384438 0.050409645 0.578180251 65 -0.259144109 0.050320742 0.03574944 0.624346804 66 -0.237355172 0.039047968 0.036302381 0.640223598 67 -0.209068768 0.037708691 0.032726765 0.570650969 68 -0.186812769 -0.103212502 0.03576446 0.676912884 69 -0.172786433 -0.322799542 0.032564533 0.565884242 70 -0.159042398 -0.574373353 0.029217968 0.635341646 71 -0.147095638 -1.013879188 0.030866113 0.634670383 72 -0.134506814 -1.329428513 0.024584343 0.577526026 73 -0.124207996 -1.42877819 0.02631154 0.565060233 74 -0.124980199 -1.472827858 0.025229417 0.614785705 75 -0.136733524 -1.242849964 0.02723085 0.459854746 76 -0.149659125 -0.963681676 0.02358622 0.558485398 77 -0.151145645 -1.043109843 0.021359816 0.555972362 78 -0.13753462 -1.214663642 0.0175342 0.56771645 79 -0.114599476 -1.036147251 0.016430437 0.495158394 80 -0.094996952 -0.283485324 0.019406977 0.462781664 81 -0.079553809 0.769093554 0.01621059 0.393319599 82 -0.064540159 1.285179236 0.016181113 0.558693723 83 -0.05142024 0.904400198 0.014401274 0.581978809 84 -0.043566842 0.226150789 0.015276027 0.497739542 85 -0.04434745 -0.601769577 0.014597293 0.639304098 86 -0.054324833 -1.123369663 0.015944878 0.479165774 87 -0.069820143 -0.926506462 0.015261844 0.440993262 88 -0.08237667 -0.630154218 0.013589098 0.495792852 89 -0.086785435 -0.65196485 0.01295334 0.503987384 90 -0.080261553 -0.966295902 0.009817103 0.52804521 91 -0.066501928 -1.280001416 0.011925537 0.495865386 92 -0.047989253 -1.235267238 0.009114033 0.448492972 93 -0.025823809 -0.793370206 0.008040574 0.407935882 94 -0.010117769 -0.289156985 0.011988093 0.448924003 95 -0.001405233 0.0357726 0.008937584 0.40814909 96 0.00271275 -0.023257982 0.007693583 0.502203702 97 -0.008418993 -0.355499091 0.007844793 0.459246902 98 -0.048371559 -0.56207407 0.007508238 0.374613555 99 -0.133519467 -0.886533046 0.005625078 0.472260951 100 -0.274066413 -1.642770421 0.006264786 0.409776142 ; 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;