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Solving a nonconvex quadratic problem Description Solve a nonconvex quadratic problem Further explanation of this example:
'Xpress Python Reference Manual'
Source Files By clicking on a file name, a preview is opened at the bottom of this page.
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 from __future__ import print_function 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]) # By default the problem is solved to global optimality. # Setting the nlpsolver control to one ensures the problem is # solved the local nonlinear solver. p.controls.nlpsolver = 1 p.optimize() | |||||||||||

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