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Solving a nonconvex quadratic problem Description Solve a nonconvex quadratic problem Further explanation of this example: 'Xpress Python Reference Manual'
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example_quadnonconvex.py # Test problem on a dot product between matrices of scalars and/or of # variables. Note that the problem cannot be solved by the Optimizer # as it is nonconvex. # # (C) Fair Isaac Corp., 1983-2024 import xpress as xp import numpy as np a = 0.1 + np.arange(21).reshape(3, 7) p = xp.problem() # Create NumPy vectors of variables y = p.addVariables(3, 7, name='') x = p.addVariables(7, 5, name='') p.addConstraint(xp.Dot(y, x) <= 0) p.addConstraint(xp.Dot(a, x) == 1) p.setObjective(x[0][0]) p.optimize() # Turns out the problem is infeasible, so let's use nonlinear IIS using the global solver to find out why # Find the first IIS and stop once it is found p.iisfirst(0) miisrow = [] miiscol = [] constrainttype = [] colbndtype = [] duals = [] rdcs = [] isolationrows = [] isolationcols = [] # get data for the IIS p.getiisdata(1, miisrow, miiscol, constrainttype, colbndtype, duals, rdcs, isolationrows, isolationcols) #print the IIS print("iis data:", miisrow, miiscol, constrainttype, colbndtype, duals, rdcs, isolationrows, isolationcols)
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