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 2.197448188 4.532818962 1.102560528 0.052167654 2 -11.98389293 4.441033165 0.952472305 0.096216327 3 -13.00165971 4.356360595 0.883489959 0.126619485 4 -12.56478905 4.246669126 0.786499234 0.177455561 5 -5.301214226 4.041043009 0.609308035 0.217547341 6 5.179054999 3.706052816 0.652242683 0.274674264 7 7.279044868 3.303158255 0.730435601 0.303514431 8 -1.316029788 2.962358601 0.832037139 0.30492268 9 -8.706244828 2.610019503 0.684835539 0.401316869 10 -7.71554091 2.390944501 0.625326533 0.370977909 11 -3.464248771 2.525926478 0.545689602 0.366199556 12 -0.18664373 2.760129022 0.555535802 0.404091812 13 -1.547598829 2.738542677 0.572299013 0.483254055 14 -1.884676989 2.460960435 0.483989948 0.475041356 15 -4.472760934 2.023649745 0.56174441 0.528554929 16 -5.529389443 1.503866973 0.394509101 0.506990655 17 -2.303243034 0.932352507 0.411341788 0.64969281 18 -3.031066627 0.856008483 0.4087031 0.446616474 19 -1.002324433 1.365590071 0.311171911 0.527389442 20 0.594213314 1.752353591 0.388673655 0.558825634 21 -1.121538796 1.790197843 0.352649843 0.580960617 22 -0.753675644 1.364513902 0.335545191 0.672562025 23 -0.54943503 0.810364712 0.341785709 0.610498094 24 -1.776855121 0.478085515 0.332613603 0.599839697 25 -3.082678928 0.210974544 0.309472198 0.619610167 26 -2.392695826 -0.151301912 0.259740872 0.66999926 27 -1.255014208 -0.394180534 0.258017846 0.586745566 28 -2.241213784 -0.473978748 0.255298168 0.665196218 29 -2.269804393 -0.332524762 0.205076796 0.541639407 30 -0.546907082 -0.117185414 0.200000194 0.64202949 31 0.532548691 -0.069997929 0.203171921 0.590157924 32 0.859119806 -0.142008084 0.203449648 0.612550373 33 -0.618586335 -0.440692667 0.226427306 0.677218789 34 -2.481579593 -0.56062672 0.197231738 0.586967721 35 -1.7859705 -0.1944613 0.16606931 0.598028314 36 0.508506027 0.571638421 0.154885091 0.564612982 37 1.022723578 1.539664374 0.181336213 0.518273875 38 -1.366871773 1.992178401 0.190434986 0.657764996 39 -2.733216282 1.574308019 0.144642426 0.74622494 40 -1.733445291 1.011683283 0.128842672 0.656580016 41 -0.025359468 0.848012427 0.110539754 0.653014705 42 0.380464556 0.977973063 0.134386253 0.598301324 43 -0.400997549 0.865288547 0.119852074 0.773232753 44 -1.091347636 0.5477308 0.123710055 0.649924276 45 -1.001914745 0.261175273 0.095818079 0.751381202 46 -0.40924566 0.055498223 0.102668462 0.687811942 47 -0.122833817 0.163942355 0.089130351 0.644628182 48 -0.427854011 0.203885321 0.102283084 0.731513771 49 -0.775088928 0.022772146 0.081536696 0.722552964 50 -0.378544043 -0.109958903 0.081367138 0.648252103 51 -0.045261081 -0.399153257 0.075365483 0.737646145 52 -0.242519242 -0.948759424 0.081655562 0.766149043 53 -0.822968812 -1.145687799 0.073677433 0.643195208 54 -0.724151216 -0.810255671 0.060456058 0.627953022 55 -0.295833859 -0.424724104 0.059882379 0.667227491 56 0.040992321 -0.244572521 0.054450317 0.660442288 57 -0.078524365 -0.289460559 0.060768838 0.685847408 58 -0.684107024 -0.441682754 0.056849362 0.614964519 59 -0.656474367 -0.805852112 0.043780002 0.672357071 60 0.034160702 -1.508784366 0.040293662 0.689190177 61 0.283592463 -2.159782094 0.047168492 0.630996917 62 -0.150901065 -2.432247468 0.048192142 0.625561829 63 -0.583359768 -2.122148661 0.043578713 0.535384832 64 -0.43324907 -1.301947691 0.034472935 0.536832957 65 0.079965599 -0.315381115 0.032761375 0.515800297 66 0.065185654 0.527324587 0.04008702 0.525302296 67 -0.182059735 0.889253163 0.034580744 0.586532057 68 -0.091556738 0.783105886 0.032091593 0.496015916 69 -0.19532615 -0.035691404 0.035933701 0.719184036 70 -0.233921743 -1.136431863 0.027800672 0.626071953 71 -0.05802121 -1.343307102 0.029122934 0.45899642 72 -0.085123238 -0.840310539 0.028475261 0.507971215 73 -0.209700089 -0.340710336 0.028132806 0.563776543 74 -0.103049737 0.130132394 0.022620523 0.4686165 75 0.081274211 0.36348662 0.024368603 0.535246252 76 -0.197082249 -0.020851936 0.028532001 0.617333273 77 -0.280963718 -0.59126486 0.01806839 0.543106112 78 -0.112472652 -0.86567078 0.021130296 0.544010783 79 -0.155050023 -0.71526282 0.01882137 0.488817164 80 -0.106227501 -0.228240391 0.016809058 0.508819085 81 0.038578279 0.382855026 0.01598085 0.462072507 82 0.085510484 0.777831429 0.017406601 0.549109908 83 -0.11609971 0.805290578 0.019424905 0.501589607 84 -0.183597852 0.456425732 0.013812537 0.56168828 85 -0.071709472 -0.290286388 0.015044122 0.580323264 86 0.011314088 -1.055035416 0.012817217 0.567133273 87 -0.021728747 -1.393895951 0.015466782 0.505778609 88 -0.127191363 -1.173115935 0.012954002 0.477766001 89 -0.083907204 -0.61714395 0.011525373 0.437668494 90 -0.043536043 -0.209140017 0.011806629 0.500173567 91 -0.035588711 -0.232783474 0.010570343 0.536943206 92 -0.072517988 -0.378308636 0.011175381 0.469017662 93 -0.107722137 -0.483407562 0.009393849 0.472887456 94 -0.027938985 -0.705875296 0.008084097 0.506295193 95 0.024212644 -0.935734792 0.008875032 0.513428362 96 -0.056139838 -0.753167888 0.0095261 0.401960123 97 -0.072027451 -0.23179516 0.006900598 0.473334687 98 -0.049851041 0.412638101 0.007276068 0.468822594 99 -0.124396831 1.345346761 0.007806209 0.448718643 100 -0.226252624 2.619687928 0.005451985 0.491716649 ; 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;