* NLP written by GAMS Convert at 10/06/06 11:33:39 * * Equation counts * Total E G L N X C * 1 1 0 0 0 0 0 * * Variable counts * x b i s1s s2s sc si * Total cont binary integer sos1 sos2 scont sint * 4 4 0 0 0 0 0 0 * FX 0 0 0 0 0 0 0 0 * * Nonzero counts * Total const NL DLL * 4 1 3 0 * * Solve m using NLP minimizing objvar; Variables x1,x2,x3,objvar; Positive Variables x2,x3; Equations e1; e1.. - (sqr((-0.01) + exp(-exp(log(62.5673411864701 - x2)*x3)/x1)) + sqr((- 0.02) + exp(-exp(log(58.6962007027177 - x2)*x3)/x1)) + sqr((-0.03) + exp(- exp(log(56.3256923849791 - x2)*x3)/x1)) + sqr((-0.04) + exp(-exp(log( 54.5880369007321 - x2)*x3)/x1)) + sqr((-0.05) + exp(-exp(log( 53.2043006187854 - x2)*x3)/x1)) + sqr((-0.06) + exp(-exp(log( 52.0480168209509 - x2)*x3)/x1)) + sqr((-0.07) + exp(-exp(log( 51.0507685839177 - x2)*x3)/x1)) + sqr((-0.08) + exp(-exp(log( 50.1712314272176 - x2)*x3)/x1)) + sqr((-0.09) + exp(-exp(log( 49.3824748381574 - x2)*x3)/x1)) + sqr((-0.1) + exp(-exp(log( 48.6659419747082 - x2)*x3)/x1)) + sqr((-0.11) + exp(-exp(log( 48.008287093122 - x2)*x3)/x1)) + sqr((-0.12) + exp(-exp(log( 47.3995812377531 - x2)*x3)/x1)) + sqr((-0.13) + exp(-exp(log( 46.8322311525364 - x2)*x3)/x1)) + sqr((-0.14) + exp(-exp(log( 46.3002956529795 - x2)*x3)/x1)) + sqr((-0.15) + exp(-exp(log( 45.7990357915906 - x2)*x3)/x1)) + sqr((-0.16) + exp(-exp(log( 45.3246088294447 - x2)*x3)/x1)) + sqr((-0.17) + exp(-exp(log( 44.8738540529253 - x2)*x3)/x1)) + sqr((-0.18) + exp(-exp(log( 44.4441391640996 - x2)*x3)/x1)) + sqr((-0.19) + exp(-exp(log( 44.0332477451615 - x2)*x3)/x1)) + sqr((-0.2) + exp(-exp(log( 43.6392952581493 - x2)*x3)/x1)) + sqr((-0.21) + exp(-exp(log( 43.2606652970159 - x2)*x3)/x1)) + sqr((-0.22) + exp(-exp(log( 42.8959604887535 - x2)*x3)/x1)) + sqr((-0.23) + exp(-exp(log( 42.5439641718685 - x2)*x3)/x1)) + sqr((-0.24) + exp(-exp(log( 42.203610125731 - x2)*x3)/x1)) + sqr((-0.25) + exp(-exp(log( 41.8739583976686 - x2)*x3)/x1)) + sqr((-0.26) + exp(-exp(log( 41.5541758068136 - x2)*x3)/x1)) + sqr((-0.27) + exp(-exp(log( 41.2435200761656 - x2)*x3)/x1)) + sqr((-0.28) + exp(-exp(log( 40.9413268091141 - x2)*x3)/x1)) + sqr((-0.29) + exp(-exp(log( 40.6469987175967 - x2)*x3)/x1)) + sqr((-0.3) + exp(-exp(log( 40.3599966485633 - x2)*x3)/x1)) + sqr((-0.31) + exp(-exp(log( 40.0798320585662 - x2)*x3)/x1)) + sqr((-0.32) + exp(-exp(log( 39.8060606634328 - x2)*x3)/x1)) + sqr((-0.33) + exp(-exp(log( 39.5382770482545 - x2)*x3)/x1)) + sqr((-0.34) + exp(-exp(log( 39.2761100673859 - x2)*x3)/x1)) + sqr((-0.35) + exp(-exp(log( 39.0192188983745 - x2)*x3)/x1)) + sqr((-0.36) + exp(-exp(log( 38.7672896403035 - x2)*x3)/x1)) + sqr((-0.37) + exp(-exp(log( 38.5200323678215 - x2)*x3)/x1)) + sqr((-0.38) + exp(-exp(log( 38.2771785685081 - x2)*x3)/x1)) + sqr((-0.39) + exp(-exp(log( 38.0384789042332 - x2)*x3)/x1)) + sqr((-0.4) + exp(-exp(log( 37.8037012475483 - x2)*x3)/x1)) + sqr((-0.41) + exp(-exp(log( 37.5726289524971 - x2)*x3)/x1)) + sqr((-0.42) + exp(-exp(log( 37.3450593259804 - x2)*x3)/x1)) + sqr((-0.43) + exp(-exp(log( 37.1208022712895 - x2)*x3)/x1)) + sqr((-0.44) + exp(-exp(log( 36.8996790799037 - x2)*x3)/x1)) + sqr((-0.45) + exp(-exp(log( 36.6815213513167 - x2)*x3)/x1)) + sqr((-0.46) + exp(-exp(log( 36.4661700236862 - x2)*x3)/x1)) + sqr((-0.47) + exp(-exp(log( 36.2534745006026 - x2)*x3)/x1)) + sqr((-0.48) + exp(-exp(log( 36.0432918613478 - x2)*x3)/x1)) + sqr((-0.49) + exp(-exp(log( 35.8354861437448 - x2)*x3)/x1)) + sqr((-0.5) + exp(-exp(log( 35.6299276901365 - x2)*x3)/x1)) + sqr((-0.51) + exp(-exp(log( 35.4264925482357 - x2)*x3)/x1)) + sqr((-0.52) + exp(-exp(log( 35.2250619195877 - x2)*x3)/x1)) + sqr((-0.53) + exp(-exp(log( 35.025521649224 - x2)*x3)/x1)) + sqr((-0.54) + exp(-exp(log( 34.8277617507753 - x2)*x3)/x1)) + sqr((-0.55) + exp(-exp(log( 34.6316759618838 - x2)*x3)/x1)) + sqr((-0.56) + exp(-exp(log( 34.4371613252136 - x2)*x3)/x1)) + sqr((-0.57) + exp(-exp(log( 34.2441177907303 - x2)*x3)/x1)) + sqr((-0.58) + exp(-exp(log( 34.0524478351983 - x2)*x3)/x1)) + sqr((-0.59) + exp(-exp(log( 33.8620560950504 - x2)*x3)/x1)) + sqr((-0.6) + exp(-exp(log( 33.672849008909 - x2)*x3)/x1)) + sqr((-0.61) + exp(-exp(log( 33.4847344660903 - x2)*x3)/x1)) + sqr((-0.62) + exp(-exp(log( 33.2976214573988 - x2)*x3)/x1)) + sqr((-0.63) + exp(-exp(log( 33.1114197244154 - x2)*x3)/x1)) + sqr((-0.64) + exp(-exp(log( 32.9260394032886 - x2)*x3)/x1)) + sqr((-0.65) + exp(-exp(log( 32.741390658749 - x2)*x3)/x1)) + sqr((-0.66) + exp(-exp(log( 32.5573833036609 - x2)*x3)/x1)) + sqr((-0.67) + exp(-exp(log( 32.3739263988872 - x2)*x3)/x1)) + sqr((-0.68) + exp(-exp(log( 32.1909278275376 - x2)*x3)/x1)) + sqr((-0.69) + exp(-exp(log( 32.008293836772 - x2)*x3)/x1)) + sqr((-0.7) + exp(-exp(log( 31.8259285391741 - x2)*x3)/x1)) + sqr((-0.71) + exp(-exp(log( 31.6437333642475 - x2)*x3)/x1)) + sqr((-0.72) + exp(-exp(log( 31.4616064487123 - x2)*x3)/x1)) + sqr((-0.73) + exp(-exp(log( 31.279441951896 - x2)*x3)/x1)) + sqr((-0.74) + exp(-exp(log( 31.0971292794385 - x2)*x3)/x1)) + sqr((-0.75) + exp(-exp(log( 30.9145521945707 - x2)*x3)/x1)) + sqr((-0.76) + exp(-exp(log( 30.7315877910617 - x2)*x3)/x1)) + sqr((-0.77) + exp(-exp(log( 30.5481052951594 - x2)*x3)/x1)) + sqr((-0.78) + exp(-exp(log( 30.3639646548686 - x2)*x3)/x1)) + sqr((-0.79) + exp(-exp(log( 30.1790148628897 - x2)*x3)/x1)) + sqr((-0.8) + exp(-exp(log( 29.9930919432498 - x2)*x3)/x1)) + sqr((-0.81) + exp(-exp(log( 29.8060165092927 - x2)*x3)/x1)) + sqr((-0.82) + exp(-exp(log( 29.6175907695704 - x2)*x3)/x1)) + sqr((-0.83) + exp(-exp(log( 29.4275948141543 - x2)*x3)/x1)) + sqr((-0.84) + exp(-exp(log( 29.23578195057 - x2)*x3)/x1)) + sqr((-0.85) + exp(-exp(log( 29.0418727657072 - x2)*x3)/x1)) + sqr((-0.86) + exp(-exp(log( 28.8455474509928 - x2)*x3)/x1)) + sqr((-0.87) + exp(-exp(log( 28.6464357147701 - x2)*x3)/x1)) + sqr((-0.88) + exp(-exp(log( 28.444103269613 - x2)*x3)/x1)) + sqr((-0.89) + exp(-exp(log( 28.2380333359004 - x2)*x3)/x1)) + sqr((-0.9) + exp(-exp(log( 28.0276006831001 - x2)*x3)/x1)) + sqr((-0.91) + exp(-exp(log( 27.8120341167232 - x2)*x3)/x1)) + sqr((-0.92) + exp(-exp(log( 27.5903603486418 - x2)*x3)/x1)) + sqr((-0.93) + exp(-exp(log( 27.3613163946629 - x2)*x3)/x1)) + sqr((-0.94) + exp(-exp(log( 27.1232055134715 - x2)*x3)/x1)) + sqr((-0.95) + exp(-exp(log( 26.8736439496681 - x2)*x3)/x1)) + sqr((-0.96) + exp(-exp(log( 26.6090744898079 - x2)*x3)/x1)) + sqr((-0.97) + exp(-exp(log( 26.3237086364982 - x2)*x3)/x1)) + sqr((-0.98) + exp(-exp(log( 26.0067455477373 - x2)*x3)/x1)) + sqr((-0.99) + exp(-exp(log( 25.6320727288055 - x2)*x3)/x1))) + objvar =E= 0; * set non default bounds x1.lo = 0.1; x1.up = 100; x2.up = 25.6; x3.up = 5; * set non default levels x1.l = 100; x2.l = 12.5; x3.l = 3; * set non default marginals Model m / all /; m.limrow=0; m.limcol=0; $if NOT '%gams.u1%' == '' $include '%gams.u1%' Solve m using NLP minimizing objvar;