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Solving a quadratically constrained problem

Description
Define the well-known Rosenbrock function and minimize it.

Further explanation of this example: 'Xpress Python Reference Manual'

Rosenbrock_python.zip[download all files]

Source Files
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rosenbrock.py[download]





rosenbrock.py

# Define the well-known Rosenbrock function and minimize it
#
# (C) Fair Isaac Corp., 1983-2024

from __future__ import print_function

import xpress as xp

x = xp.var(lb=-xp.infinity)
y = xp.var(lb=-xp.infinity)

p = xp.problem()

p.addVariable(x, y)

# parameters of the Rosenbrock function
a = 1
b = 100

p.setObjective((a - x)**2 + b * (y - x**2)**2)

# Solve this problem with a local nonlinear solver.
p.controls.nlpsolver = 1

p.optimize()

print('solution: ', p.getSolution(), '; value: ', p.getObjVal())

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