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## st_e41.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.
• Kim, Y S, Problems in reliability, 1998. Personal Communication

Point:

* NLP written by GAMS Convert at 08/29/02 12:49:54 * * Equation counts * Total E G L N X C * 3 1 0 2 0 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 * 13 1 12 0 * * Solve m using NLP minimizing objvar; Variables x1,x2,x3,x4,objvar; Equations e1,e2,e3; e1.. - (-x3*sqr(1 - x1)*sqr(1 - x4) - (1 - x3)*sqr(1 - x2*(1 - (1 - x1)*(1 - x4)))) =L= 0.1; e2.. (-x3*sqr(1 - x1)*sqr(1 - x4)) - (1 - x3)*sqr(1 - x2*(1 - (1 - x1)*(1 - x4) )) =L= 0; e3.. - (200*x1**0.6 + 200*x2**0.6 + 200*x3**0.6 + 300*x4**0.6) + objvar =E= 0; * set non default bounds x1.lo = 0.5; x1.up = 1; x2.lo = 0.5; x2.up = 1; x3.lo = 0.5; x3.up = 1; x4.lo = 0.5; x4.up = 1; * 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;