Steve Jacobsen (jacobsen@ee.ucla.edu), Khosrow Moshirvaziri (moshir@ee.ucla.edu) LINEAR REVERSE CONVEX MINIMIZATION PROBLEM (m=10, n=20): min cx Ax < b x > 0 g(x) < 0 where g(x) = -x'x + d'x + g0 A,b = -6 -9 9 -5 10 5 -9 9 -9 5 7 -7 8 -10 3 2 -0 2 -7 -5 -1 -9 1 7 -9 4 -0 8 -9 5 5 -2 1 2 -2 -7 9 -1 6 9 -7 18 4 3 1 5 5 -5 0 0 5 10 7 6 7 -9 4 1 9 -5 -2 6 56 4 -10 -8 -3 3 -5 0 -2 7 8 -5 -9 -7 4 -2 -7 -7 -0 -7 -1 -43 9 -2 3 3 -9 -3 -4 -4 -7 -5 -2 1 -6 9 -2 10 -6 -2 8 -3 -8 -2 -9 -2 5 3 -7 10 8 -10 -4 1 -0 4 -5 -0 -2 -4 -6 -8 -1 -22 0 -2 4 10 8 -0 -0 1 4 -3 -1 9 -7 -6 -7 -7 3 -9 -7 6 0 7 4 8 -3 -5 8 -5 -1 7 0 -4 5 -8 -4 2 1 -7 8 -9 9 20 2 7 9 3 9 5 5 6 8 8 5 10 6 5 8 7 7 10 10 9 1430 -20 2 -26 -73 -65 30 -2 -6 -40 -34 -28 -69 0 73 16 30 -54 66 51 -58 1000 c= 1 0 -8 -2 2 8 -1 5 7 4 6 4 5 -10 8 0 -1 -9 4 -0 g0=-1.364305082996628e+07 d= -2.015953880210081e+04 7.636082173066256e+03 1.508958077609551e+05 3.871979066339105e+04 -4.098920272103873e+04 -1.464818430188668e+05 1.730476763886910e+04 -9.751292264656250e+04 -1.295302563525743e+05 -7.712685827120741e+04 -1.134588710986231e+05 -7.173838960635096e+04 -9.607192004020569e+04 1.916802488463171e+05 -1.516164100084949e+05 1.338280917765579e+03 2.364595866452542e+04 1.709434060607900e+05 -6.829304416404771e+04 -3.177704507367769e+02 optimal x = x(1) = 1.428650889386982e+01 x(2) = 0.000000000000000e+00 x(3) = 1.377063794230816e+01 x(4) = 3.192824460102860e+01 x(5) = 3.513491584539399e+01 x(6) = 0.000000000000000e+00 x(7) = 1.038469981175697e+01 x(8) = 4.230478189797566e+00 x(9) = 0.000000000000000e+00 x(10) = 0.000000000000000e+00 x(11) = 0.000000000000000e+00 x(12) = 0.000000000000000e+00 x(13) = 1.766887048378935e+01 x(14) = 3.546095378680057e+01 x(15) = 0.000000000000000e+00 x(16) = 0.000000000000000e+00 x(17) = 0.000000000000000e+00 x(18) = 4.211525039247857e+01 x(19) = 0.000000000000000e+00 x(20) = 9.301711151196521e+00