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 -4.757186495 4.708924892 0.95123863 0.04851469 2 -4.53358102 4.44129989 0.904835 0.0942052 3 -4.303760322 4.166637319 0.8606971 0.13718602 4 -4.093132358 3.915431659 0.81872404 0.17758226 5 -3.893501899 3.67784691 0.7787988 0.21553881 6 -3.703843274 3.452599896 0.74081904 0.2511824 7 -3.523233459 3.238549847 0.70469123 0.2846288 8 -3.35143065 3.035389989 0.67032504 0.31598967 9 -3.187964055 2.842542944 0.6376348 0.345371 10 -3.032473586 2.659547459 0.6065392 0.37287334 11 -2.884527356 2.485864336 0.5769601 0.3985931 12 -2.743734807 2.321018589 0.5488246 0.42262033 13 -2.609999477 2.164882026 0.52206206 0.44504228 14 -2.483001311 2.017051815 0.4966024 0.46594536 15 -2.362156299 1.876810319 0.47238138 0.48540878 16 -2.246976397 1.743542811 0.44934 0.5035053 17 -2.137540724 1.617343351 0.42742303 0.5203028 18 -2.033435702 1.497703482 0.40657148 0.53587395 19 -1.93409094 1.383914983 0.38673794 0.550277 20 -1.839752304 1.276276379 0.36787334 0.5635723 21 -1.749995815 1.174260205 0.3499276 0.5758213 22 -1.66450589 1.077481347 0.33285898 0.58707523 23 -1.5832996 0.985959877 0.3166234 0.5973882 24 -1.506018838 0.899238907 0.3011798 0.60681057 25 -1.432530765 0.817157675 0.28649038 0.61538845 26 -1.362670153 0.739523121 0.27251714 0.62316847 27 -1.296180573 0.666004365 0.25922564 0.63019276 28 -1.232978125 0.596490781 0.24658263 0.63650185 29 -1.172860352 0.530743663 0.23455578 0.64213514 30 -1.11564562 0.46853884 0.22311568 0.6471286 31 -1.061260692 0.409767618 0.2122335 0.6515173 32 -1.009495202 0.354176252 0.20188166 0.65533465 33 -0.960266809 0.301677763 0.19203515 0.6586111 34 -0.913476437 0.252133742 0.18266827 0.66137797 35 -0.868911051 0.205278638 0.17375812 0.66366285 36 -0.826480504 0.161006524 0.16528289 0.6654922 37 -0.786122962 0.119237771 0.15722162 0.6668913 38 -0.74774594 0.079854621 0.14955384 0.6678849 39 -0.711254877 0.042745575 0.14226043 0.66849595 40 -0.676541532 0.007776591 0.13532281 0.66874695 41 -0.643480967 -0.025211608 0.128724 0.6686582 42 -0.612061009 -0.056231005 0.122447744 0.66824925 43 -0.582267204 -0.085303285 0.1164775 0.6675399 44 -0.553875765 -0.112704984 0.11079761 0.6665489 45 -0.526827776 -0.138500212 0.10539542 0.66529125 46 -0.501167446 -0.162642473 0.10025654 0.66378427 47 -0.476776659 -0.185285607 0.09536785 0.6620434 48 -0.453550929 -0.206543316 0.09071707 0.66008323 49 -0.431442134 -0.226478143 0.08629309 0.65791696 50 -0.4104187 -0.245138139 0.08208463 0.6555579 51 -0.390414283 -0.262600293 0.07808131 0.6530182 52 -0.371386545 -0.278919838 0.074273095 0.6503097 53 -0.353276355 -0.294162243 0.07065051 0.6474434 54 -0.33603772 -0.308387362 0.06720465 0.64442986 55 -0.319639735 -0.321637099 0.06392696 0.6412789 56 -0.304039033 -0.33396411 0.060809195 0.6380002 57 -0.289195547 -0.345415302 0.057843644 0.63460255 58 -0.275081356 -0.356019952 0.055022858 0.6310947 59 -0.261670801 -0.365822214 0.052339703 0.6274848 60 -0.248893395 -0.374899983 0.049787305 0.6237807 61 -0.236704259 -0.383304028 0.04735982 0.6199891 62 -0.225127927 -0.391019365 0.045051202 0.6161169 63 -0.214145629 -0.398062587 0.042855304 0.61217093 64 -0.203723143 -0.404462316 0.040766444 0.60815775 65 -0.193822727 -0.410278168 0.03877913 0.6040836 66 -0.184337307 -0.415641131 0.0368885 0.59995383 67 -0.175301092 -0.420509316 0.03509087 0.59577245 68 -0.166761532 -0.424819585 0.033380903 0.5915454 69 -0.158651032 -0.428654605 0.0317542 0.58727765 70 -0.15096359 -0.43203094 0.030206513 0.5829738 71 -0.143605852 -0.435047626 0.02873376 0.5786383 72 -0.136576485 -0.437716604 0.02733326 0.57427406 73 -0.129925213 -0.43998011 0.026001034 0.56988525 74 -0.123604018 -0.441889704 0.024733651 0.56547564 75 -0.117597802 -0.443462648 0.023527907 0.56104857 76 -0.111879048 -0.444732101 0.022380732 0.5566074 77 -0.106421199 -0.445740698 0.021289432 0.55215484 78 -0.10122906 -0.446470918 0.020251427 0.5476935 79 -0.09629784 -0.446932561 0.019263994 0.5432263 80 -0.091607328 -0.447153286 0.018324666 0.53875566 81 -0.087146579 -0.447143071 0.017431086 0.534284 82 -0.082891812 -0.446925626 0.016581032 0.5298135 83 -0.078840017 -0.446506993 0.015772568 0.52534616 84 -0.074993799 -0.445899099 0.015003558 0.520884 85 -0.07133744 -0.445098939 0.014272061 0.5164288 86 -0.067867254 -0.444114225 0.01357621 0.5119826 87 -0.064540932 -0.443015392 0.012914204 0.50754696 88 -0.06135609 -0.441785801 0.012284893 0.50312275 89 -0.058344528 -0.440386941 0.011686537 0.49871176 90 -0.055489703 -0.438849432 0.011117484 0.49431548 91 -0.052781246 -0.437180487 0.010576247 0.48993522 92 -0.050215584 -0.435379884 0.010061385 0.4855723 93 -0.047791966 -0.433450115 0.009571486 0.48122802 94 -0.045480018 -0.431433965 0.009105167 0.4769036 95 -0.043249195 -0.429367992 0.008661568 0.47259957 96 -0.041130196 -0.427204471 0.008239832 0.46831656 97 -0.039135371 -0.42493579 0.00783858 0.4640558 98 -0.037185423 -0.422503718 0.00745678 0.45981812 99 -0.03544293 -0.420161591 0.00709344 0.4556043 100 -0.034132147 -0.418256404 0.006747611 0.45141503 ; 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;