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## st_e42.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.
• Tawarmalani, M, and Ahmed, S, Analysis of a machining process, 1997. Project Report on Design of Experiments

Point:

* NLP written by GAMS Convert at 08/29/02 12:49:54 * * Equation counts * Total E G L N X C * 3 3 0 0 0 0 0 * * Variable counts * x b i s1s s2s sc si * Total cont binary integer sos1 sos2 scont sint * 8 8 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,x6,x7,objvar; Positive Variables x1,x2,x3,x4,x7; Equations e1,e2,e3; e1.. 51.5712*x3*x5 + 20.7324*x3 - 25.7856*x5 + 14.9251*x3*x7 - 22.2988*x7 - 10.1409*x6*x7 + 42.3401*x6 - x1 + x2 - 6.6425*x4 =E= -72.82; e2.. x3 =E= 1; e3.. - x1 - x2 + objvar =E= 0; * set non default bounds x3.up = 1; x4.up = 1; x5.lo = -1; x5.up = 1; x6.lo = -1; x6.up = 1; x7.up = 3; * 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;