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st_e05.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.
• Liebman, J, Lasdon, L S, Schrage, L, and Waren, A D, Modeling and Optimization with GINO. The Scientific Press, Palo Alto, CA, 1986.

Point:

* NLP written by GAMS Convert at 08/29/02 12:49:53 * * Equation counts * Total E G L N X C * 4 4 0 0 0 0 0 * * Variable counts * x b i s1s s2s sc si * Total cont binary integer sos1 sos2 scont sint * 6 6 0 0 0 0 0 0 * FX 0 0 0 0 0 0 0 0 * * Nonzero counts * Total const NL DLL * 11 7 4 0 * * Solve m using NLP minimizing objvar; Variables x1,x2,x3,x4,x5,objvar; Positive Variables x1,x2,x3; Equations e1,e2,e3,e4; e1.. 100000*x4 - 120*x1*(300 - x4) =E= 10000000; e2.. 100000*x5 - 80*x2*(400 - x5) - 100000*x4 =E= 0; e3.. - 4000*x3 - 100000*x5 =E= -50000000; e4.. - x1 - x2 - x3 + objvar =E= 0; * set non default bounds x1.up = 15834; x2.up = 36250; x3.up = 10000; x4.lo = 100; x4.up = 300; x5.lo = 100; x5.up = 400; * 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;