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 -7.2722489 5.073838243 0.806713689 0.039563997 2 -5.856894255 4.469820967 0.967808646 0.137810958 3 -4.897965408 3.937622776 0.740577748 0.153319458 4 -4.515806656 3.54561314 1.14937635 0.166580413 5 -4.015063862 3.278505653 0.499412591 0.171010037 6 -3.113517841 3.022071346 0.64310389 0.306610857 7 -2.617512732 2.796958578 0.81341851 0.304103611 8 -2.367532409 2.754619151 0.560346004 0.172909976 9 -2.279578019 2.702911067 0.639916025 0.282977255 10 -2.59189334 2.312031594 0.685939454 0.594362263 11 -3.100697168 1.917628313 0.722088501 0.397655107 12 -3.257246346 1.978894187 0.447063739 0.253611158 13 -2.969269169 2.26759808 0.504324723 0.366001408 14 -2.539622885 2.42543918 0.449755662 0.426815045 15 -2.113444724 2.325725328 0.461589025 0.552839667 16 -1.815365454 2.093056856 0.482545048 0.487115931 17 -1.57672139 1.877666348 0.374540947 0.530872922 18 -1.45856076 1.714352066 0.471632278 0.533959973 19 -1.468222078 1.654312068 0.41974185 0.444587818 20 -1.421510403 1.530318953 0.333121762 0.695764455 21 -1.414623374 1.407915645 0.369240229 0.533754942 22 -1.600159253 1.458324662 0.398380746 0.532663848 23 -1.889474805 1.506272458 0.379511611 0.620685094 24 -2.084863938 1.480750022 0.341430018 0.598685801 25 -2.03870513 1.375950807 0.282766095 0.551199726 26 -1.746700064 1.007517201 0.238719639 0.639009383 27 -1.365564227 0.215737441 0.270844354 0.896514549 28 -0.993967122 -0.569407673 0.223594412 0.705407134 29 -0.699436597 -0.805927338 0.218977201 0.558004485 30 -0.630998429 -0.545941654 0.264383817 0.534589218 31 -0.795524261 -0.123993039 0.273654958 0.620388078 32 -1.025585509 0.256712044 0.225939175 0.44877483 33 -1.21112056 0.242658373 0.270895174 0.899103105 34 -1.197122854 -0.023302891 0.126799167 0.688397572 35 -1.022474752 0.027097405 0.17454655 0.509242337 36 -0.913178626 0.256958282 0.16843268 0.681545179 37 -0.935733763 0.514880503 0.207989309 0.474357331 38 -1.023163399 0.5769523 0.164547306 0.745672926 39 -1.070101802 0.317587089 0.1330465 0.644234164 40 -1.111331216 -0.100992014 0.15032244 0.674365733 41 -1.163460145 -0.655911062 0.145263578 0.717047917 42 -1.154898037 -1.188399384 0.126920151 0.782348081 43 -1.015086327 -1.321192593 0.069246424 0.559428874 44 -0.810390664 -0.921216254 0.133468595 0.470976698 45 -0.539087109 -0.373249419 0.031796917 0.651466998 46 -0.254635077 0.136455557 0.10245195 0.554536877 47 -0.062640231 0.586192735 0.065778421 0.718314628 48 0.032055444 1.070343005 0.084274146 0.41523402 49 -0.018109512 1.410278947 0.110430259 0.770891182 50 -0.146832997 1.484465394 0.07365495 0.695729656 51 -0.313602594 1.628508426 0.10802049 0.507844189 52 -0.47640283 1.648881584 0.085836087 0.609048756 53 -0.546129481 1.137384774 0.067168074 0.755937129 54 -0.514929386 0.077427862 0.055060344 0.9571672 55 -0.426867137 -0.956761097 0.057586655 0.59624965 56 -0.324827418 -1.682347158 0.06536374 0.814338586 57 -0.203698382 -2.041793441 0.030419601 0.52536772 58 -0.11168163 -2.047073759 0.061791352 0.657208196 59 -0.095616901 -1.922372768 0.055265126 0.601444527 60 -0.132464264 -1.681400954 0.057941122 0.666229854 61 -0.203870898 -1.25290973 0.066753728 0.55822428 62 -0.255126078 -0.584166402 0.042134188 0.440967845 63 -0.261926076 0.014506271 0.034451016 0.579018917 64 -0.270232733 0.291794052 0.050384342 0.661634656 65 -0.291596275 0.396227056 0.045717358 0.54293297 66 -0.294900431 0.401605352 0.035834001 0.577833744 67 -0.271700681 0.216615231 0.030925791 0.643672437 68 -0.236745283 -0.081557138 0.035042719 0.655340997 69 -0.193156113 -0.282963575 0.024579133 0.50111307 70 -0.148432073 -0.432802874 0.030605811 0.551683032 71 -0.111724747 -0.753623029 0.025067766 0.679390619 72 -0.083428715 -1.129427332 0.02285439 0.612263497 73 -0.078178821 -1.307332458 0.031034592 0.416255963 74 -0.091016073 -1.470109032 0.024883779 0.740532398 75 -0.107790661 -1.521827071 0.029885602 0.491855937 76 -0.112770927 -1.177668229 0.017517962 0.478841447 77 -0.103851466 -0.572880139 0.022312453 0.394945857 78 -0.092847216 0.023182409 0.016014094 0.535684514 79 -0.090294314 0.464495468 0.021647789 0.532067116 80 -0.103773301 0.852689551 0.023107529 0.503982581 81 -0.118091409 1.215623813 0.020999198 0.444568379 82 -0.114564043 1.392435214 0.009565987 0.353857032 83 -0.103484774 0.908301865 0.017923091 0.841865811 84 -0.097395568 -0.040503166 0.015029692 0.677236757 85 -0.089660235 -0.703794275 0.015226215 0.479350077 86 -0.075748614 -0.986367142 0.012089852 0.500219356 87 -0.054294495 -1.089627116 0.008649974 0.543978797 88 -0.037140391 -1.06378647 0.014478467 0.501901434 89 -0.027359405 -0.917506844 0.010501392 0.441822736 90 -0.021485091 -0.80630001 0.010384194 0.586657049 91 -0.025281141 -0.699334039 0.010932357 0.378394922 92 -0.042395017 -0.651239027 0.015166009 0.67564843 93 -0.062981715 -0.530383941 0.013962169 0.311524935 94 -0.067398644 -0.302897672 0.006703841 0.446063739 95 -0.054780479 -0.33099091 0.007840218 0.555076909 96 -0.036789907 -0.524901151 0.009867004 0.479360906 97 -0.014487928 -0.720851184 0.004588663 0.324555541 98 0.004762528 -1.156168984 0.009312065 0.544593428 99 0.011447286 -1.90909843 0.006646213 0.470479317 100 0.005962439 -2.802520925 0.008635989 0.377864098 ; 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;