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## st_e24.gms:

#### References:

• Tawarmalani, M, and Sahinidis, N, Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming: Theory, Algorithms, Software, and Applications. Kluwer, 2002.
• Konno, H, and Kuno, T, Linear multiplicative programming. Mathematical Programming 56 (1992), 51-64.

Point:

* NLP written by GAMS Convert at 08/29/02 12:49:54 * * Equation counts * Total E G L N X C * 5 1 1 3 0 0 0 * * Variable counts * x b i s1s s2s sc si * Total cont binary integer sos1 sos2 scont sint * 3 3 0 0 0 0 0 0 * FX 0 0 0 0 0 0 0 0 * * Nonzero counts * Total const NL DLL * 11 9 2 0 * * Solve m using NLP minimizing objvar; Variables x1,x2,objvar; Positive Variables x1; Equations e1,e2,e3,e4,e5; e1.. 2*x1 + 3*x2 =G= 9; e2.. 3*x1 - x2 =L= 8; e3.. - x1 + 2*x2 =L= 8; e4.. x1 + 2*x2 =L= 12; e5.. - ((5 + x1 - x2)*(x1 + x2 - 1) + x1) + objvar =E= 0; * set non default bounds x1.up = 4; x2.lo = 1; x2.up = 5; * set non default levels * 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;