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## ex14_2_5.gms:

#### Reference:

• Floudas, C A, Pardalos, P M, Adjiman, C S, Esposito, W R, Gumus, Z H, Harding, S T, Klepeis, J L, Meyer, C A, and Schweiger, C A, Handbook of Test Problems in Local and Global Optimization. Kluwer Academic Publishers, 1999.
• Original source: Global Model of Chapter 14 ex14.2.5.gms from Floudas e.a. Test Problems

Point: p1
Best known point: p1 with value 0.0000

* NLP written by GAMS Convert at 07/19/01 13:40:29 * * Equation counts * Total E G L N X * 6 2 0 4 0 0 * * Variable counts * x b i s1s s2s sc si * Total cont binary integer sos1 sos2 scont sint * 5 5 0 0 0 0 0 0 * FX 0 0 0 0 0 0 0 0 * * Nonzero counts * Total const NL DLL * 20 8 12 0 * * Solve m using NLP minimizing objvar; Variables x1,x2,x3,objvar,x5; Positive Variables x5; Equations e1,e2,e3,e4,e5,e6; e1.. objvar - x5 =E= 0; e2.. 0.361872516756437*x2/(x1 + 0.888649896608059*x2) + 0.868134622480909*x2/( 0.696880695582072*x1 + x2) - (0.361872516756437*x1*x2/sqr(x1 + 0.888649896608059*x2) + 0.604986259573375*x2*x1/sqr(0.696880695582072*x1 + x2)) - 2755.64173589155/(219.161 + x3) - x5 =L= -9.20816767045657; e3.. 0.868134622480909*x1/(0.696880695582072*x1 + x2) + 0.361872516756437*x1/( x1 + 0.888649896608059*x2) - (0.321577974600906*x1*x2/sqr(x1 + 0.888649896608059*x2) + 0.868134622480909*x2*x1/sqr(0.696880695582072*x1 + x2)) - 4117.06819797521/(227.438 + x3) - x5 =L= -12.6599269316621; e4.. (-0.361872516756437*x2/(x1 + 0.888649896608059*x2)) - 0.868134622480909*x2 /(0.696880695582072*x1 + x2) + 0.361872516756437*x1*x2/sqr(x1 + 0.888649896608059*x2) + 0.604986259573375*x2*x1/sqr(0.696880695582072*x1 + x2) + 2755.64173589155/(219.161 + x3) - x5 =L= 9.20816767045657; e5.. (-0.868134622480909*x1/(0.696880695582072*x1 + x2)) - 0.361872516756437*x1 /(x1 + 0.888649896608059*x2) + 0.321577974600906*x1*x2/sqr(x1 + 0.888649896608059*x2) + 0.868134622480909*x2*x1/sqr(0.696880695582072*x1 + x2) + 4117.06819797521/(227.438 + x3) - x5 =L= 12.6599269316621; e6.. x1 + x2 =E= 1; * set non default bounds x1.lo = 1E-6; x1.up = 1; x2.lo = 1E-6; x2.up = 1; x3.lo = 60; x3.up = 100; * set non default levels x1.l = 0.937; x3.l = 80.166; * 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;