Example #1
0
#
# First (minor) difference: we must import the XpressProblem class
# from xpress_problem.py in the problems/ directory.
#

# Problem data.
n = 2
numpy.random.seed(1)
x0 = numpy.arange(n)
y0 = numpy.arange(n)

# Construct the problem.
x = Variable(n)  # x_0_0, x_0_1
y = Variable(n)  # x_1_0, x_1_1

x.var_id = 'Xvar'
y.var_id = 'Y'

objective = Minimize(sum(y) + sum_squares(x))

qcon1 = sum_squares(y - y0) <= 1.01
lowx = x >= x0
upx = x <= 10 + 10 * x0
qcon2 = sum_squares(y + y0) <= 1.01

qcon1.constr_id = 'dist_pos'
lowx.constr_id = 'first_orthant'
upx.constr_id = 'upper_lim'
qcon2.constr_id = 'dist_neg'

constraints = [qcon1, lowx, qcon2, upx]
Example #2
0
from cvxpy.problems.xpress_problem import XpressProblem

import numpy

# Problem data.
n = 2
numpy.random.seed(1)
x0 = numpy.arange (n)
y0 = numpy.arange (n)

# Construct the problem.
x = Variable (n)    # x_0_0, x_0_1
y = Variable (n)    # x_1_0, x_1_1

x.var_id = 'Xvar'
y.var_id = 'Y'

objective = Minimize (sum (y) + sum_squares (x))

qcon1 = sum_squares (y - y0) <= 1.01
lowx  = x >= x0
upx   = x <= 10 + 10 * x0
qcon2 = sum_squares (y + y0) <= 1.01

qcon1.constr_id = 'dist_pos'
lowx.constr_id  = 'first_orthant'
upx.constr_id   = 'upper_lim'
qcon2.constr_id = 'dist_neg'

constraints = [qcon1, lowx, qcon2, upx]