set exp /1*20/ quantities /dZ1,dZ2,dZ3,Z1,Z2,Z3/; variables dZ1_mod, dZ2_mod, dZ3_mod, P1, P2, P3, P4, w; table meas(exp,quantities) dZ1 dZ2 dZ3 Z1 Z2 Z3 1 -3.1201 1.2452 1.8749 0.8241 0.0938 0.0821 2 -2.4704 0.6498 1.8206 0.6852 0.1345 0.1802 3 -1.9661 0.5061 1.4601 0.5747 0.1654 0.2599 4 -1.5664 0.4316 1.1348 0.4867 0.1899 0.3233 5 -1.2477 0.3517 0.8959 0.4167 0.2095 0.3739 6 -0.9935 0.2795 0.714 0.3609 0.225 0.4141 7 -0.7912 0.222 0.5692 0.3164 0.2374 0.4462 8 -0.63 0.1769 0.4531 0.2811 0.2472 0.4717 9 -0.5017 0.1413 0.3604 0.2529 0.2551 0.492 10 -0.3994 0.1128 0.2866 0.2305 0.2613 0.5082 11 -0.318 0.0901 0.2279 0.2126 0.2663 0.5211 12 -0.2532 0.0721 0.1811 0.1984 0.2702 0.5314 13 -0.2017 0.0577 0.144 0.1871 0.2734 0.5395 14 -0.1607 0.0463 0.1144 0.1781 0.2759 0.546 15 -0.128 0.0374 0.0907 0.1709 0.2779 0.5512 16 -0.102 0.0304 0.0716 0.1652 0.2795 0.5553 17 -0.0812 0.0244 0.0568 0.1606 0.2808 0.5586 18 -0.0639 0.013 0.0509 0.157 0.2818 0.5612 19 -0.0506 0.0076 0.0429 0.1541 0.2826 0.5633 20 -0.0426 0.0254 0.0172 0.1518 0.2832 0.5649 ; equations E1, E2, E3, obj; E1(exp).. dZ1_mod(exp) =E= -P1*meas(exp, 'Z1') + P2*meas(exp, 'Z2') ; E2(exp).. dZ2_mod(exp) =E= P1*meas(exp, 'Z1') - (P2+P3)*meas(exp, 'Z2') + P4*meas(exp, 'Z3') ; E3(exp).. dZ3_mod(exp) =E= P3*meas(exp, 'Z2') - P4*meas(exp, 'Z3') ; 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')) + (dZ3_mod(exp) - meas(exp, 'dZ3'))*(dZ3_mod(exp) - meas(exp, 'dZ3')) ); P1.lo = 0; P1.up = 10; P2.lo = 0; P2.up = 10; P3.lo = 10; P3.up = 50; P4.lo = 10; P4.up = 50; MODEL TEST / E1, E2, E3, obj / ; OPTION LIMROW = 0.0; OPTION LIMCOL = 0.0; *OPTION MINLP=SBB; SOLVE TEST USING NLP minimiZING w;