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 -5.358420169 3.255623592 0.980447546 0.052675953 2 -5.249838034 3.240756094 0.917066102 0.087694122 3 -5.090932334 3.20957911 0.905044203 0.143350853 4 -4.880676256 3.158830787 0.840126004 0.17936933 5 -4.571950767 3.088022948 0.705476001 0.233343824 6 -4.226582506 2.998831369 0.728792756 0.264649722 7 -3.923097685 2.894901157 0.694398888 0.310185291 8 -3.643807552 2.781589197 0.634662985 0.31182057 9 -3.446779643 2.663865986 0.744891579 0.340287089 10 -3.24520218 2.541204869 0.553422782 0.410450524 11 -2.964766279 2.422737176 0.549045902 0.313945659 12 -2.674979666 2.307071763 0.509748039 0.401295483 13 -2.378881932 2.186782517 0.460760889 0.388495455 14 -2.139628796 2.060387858 0.487055739 0.448118999 15 -1.984672483 1.922829667 0.459434813 0.516896241 16 -1.924535881 1.778960613 0.518092278 0.5450811 17 -1.907291761 1.641042988 0.416779139 0.467494998 18 -1.865462787 1.510959897 0.363303598 0.510630541 19 -1.872202297 1.382336757 0.448749717 0.557817164 20 -1.917461532 1.258667295 0.413293894 0.547123689 21 -1.907463843 1.142183057 0.341892337 0.593200655 22 -1.818642297 1.034696902 0.282725102 0.610554185 23 -1.703247118 0.946035484 0.302545443 0.541833394 24 -1.608294994 0.874602824 0.296483171 0.596080323 25 -1.538088012 0.820532533 0.29439947 0.484181811 26 -1.482739254 0.77178975 0.265399983 0.6945438 27 -1.436068813 0.725802892 0.270720273 0.590547916 28 -1.392338058 0.695202658 0.25624606 0.559876576 29 -1.316479121 0.667663144 0.205220383 0.62582846 30 -1.212515542 0.641102889 0.201965185 0.554676775 31 -1.107463241 0.60806839 0.196504746 0.65015839 32 -1.00870539 0.56310125 0.191629755 0.61859233 33 -0.917455888 0.503881064 0.185878973 0.802042023 34 -0.832216432 0.439354866 0.18289604 0.736673563 35 -0.730469947 0.400372541 0.121123704 0.497953769 36 -0.638203171 0.372743796 0.15772922 0.694862163 37 -0.599779186 0.344554225 0.176755595 0.573650701 38 -0.579373046 0.314977078 0.133600911 0.65085015 39 -0.571071929 0.270572405 0.155543687 0.679486296 40 -0.577469614 0.211897202 0.140063452 0.718751435 41 -0.575300853 0.145768063 0.128350626 0.650400692 42 -0.564978679 0.071135389 0.12468183 0.773585389 43 -0.540330838 -0.004441588 0.098248119 0.635435426 44 -0.513354471 -0.074082003 0.109860933 0.688379184 45 -0.504851893 -0.144966675 0.12230028 0.709515429 46 -0.4982157 -0.209784358 0.101242541 0.669438955 47 -0.481070399 -0.267467798 0.095762421 0.720366298 48 -0.455622912 -0.314470817 0.084056903 0.681417987 49 -0.427507713 -0.343431482 0.086027189 0.606326653 50 -0.404230771 -0.356110935 0.083991842 0.537205224 51 -0.384894269 -0.375327318 0.0814106 0.774387702 52 -0.366567011 -0.399028141 0.071504129 0.610996522 53 -0.349023769 -0.416262858 0.068979946 0.654135357 54 -0.342266384 -0.436016844 0.080804794 0.68072202 55 -0.33293264 -0.452397734 0.04948999 0.648563636 56 -0.326058463 -0.460182905 0.074366275 0.58027865 57 -0.32672499 -0.46478481 0.059796235 0.604921263 58 -0.320527159 -0.473972332 0.060525478 0.623212962 59 -0.304000999 -0.492623379 0.043629516 0.720287197 60 -0.278524643 -0.508783855 0.046849682 0.570084679 61 -0.254066699 -0.518479022 0.046042913 0.66863769 62 -0.231689828 -0.524221847 0.046955587 0.635131693 63 -0.207754942 -0.515276752 0.035697608 0.597854698 64 -0.185698426 -0.489832972 0.042689129 0.543877133 65 -0.168070096 -0.453706714 0.034075814 0.586919111 66 -0.154308142 -0.413654526 0.037132665 0.594752813 67 -0.148812564 -0.365630014 0.037380044 0.50822994 68 -0.147917953 -0.317985278 0.034472659 0.602913852 69 -0.149758961 -0.275390556 0.035192016 0.538986204 70 -0.15201797 -0.237132227 0.033245521 0.577479821 71 -0.149289478 -0.209206684 0.026863457 0.598092892 72 -0.141941469 -0.186078303 0.028035878 0.522322124 73 -0.131412979 -0.169789347 0.023545554 0.553457945 74 -0.11798233 -0.169000188 0.021464385 0.585270836 75 -0.107445231 -0.178701074 0.025703829 0.458047955 76 -0.100394228 -0.208852269 0.022380844 0.614270586 77 -0.09472823 -0.269055135 0.021172513 0.686022636 78 -0.092098391 -0.339107626 0.02209659 0.600239242 79 -0.091848268 -0.402624056 0.0204094 0.526072735 80 -0.092361274 -0.46205169 0.018966398 0.561847949 81 -0.093850976 -0.517040504 0.01961041 0.478932991 82 -0.095298601 -0.574724571 0.018122719 0.629305347 83 -0.094606804 -0.633995258 0.016150736 0.574765705 84 -0.091119763 -0.68045094 0.013967771 0.561895582 85 -0.085695623 -0.707609302 0.01334216 0.471196131 86 -0.080722766 -0.717902873 0.015194633 0.528363439 87 -0.074898597 -0.715054598 0.010832653 0.479210903 88 -0.068463946 -0.698398058 0.012254842 0.487454027 89 -0.062744403 -0.672404913 0.009409009 0.470284695 90 -0.058919811 -0.638668605 0.01225202 0.44361188 91 -0.057874779 -0.602660037 0.011487619 0.445412573 92 -0.056820789 -0.572379978 0.010062554 0.475380267 93 -0.054979523 -0.547866164 0.009503684 0.39947392 94 -0.051305342 -0.536628053 0.006841364 0.50588029 95 -0.047189472 -0.541432276 0.009164954 0.467032428 96 -0.042996805 -0.555860336 0.006433302 0.501059396 97 -0.038035471 -0.575929531 0.006020594 0.476569002 98 -0.034739455 -0.594088807 0.007516384 0.482546334 99 -0.033182719 -0.604321348 0.006420641 0.388032668 100 -0.03240567 -0.601531006 0.007025269 0.405358762 ; 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;