doc/source/examples/dgp/max_volume_box.rst
This example is adapted from Boyd, Kim, Vandenberghe, and Hassibi, "A Tutorial on Geometric Programming <https://web.stanford.edu/~boyd/papers/pdf/gp_tutorial.pdf>__\ ".
In this example, we maximize the shape of a box with height :math:h,
width :math:w, and depth :math:d, with limits on the wall area
:math:2(hw + hd) and the floor area :math:wd, subject to bounds on
the aspect ratios :math:h/w and :math:w/d. The optimization problem
is
.. math::
\begin{array}{ll} \mbox{maximize} & hwd \ \mbox{subject to} & 2(hw + hd) \leq A_{\text wall}, \ & wd \leq A_{\text flr}, \ & \alpha \leq h/w \leq \beta, \ & \gamma \leq d/w \leq \delta. \end{array}
.. code:: python
import cvxpy as cp
# Problem data.
A_wall = 100
A_flr = 10
alpha = 0.5
beta = 2
gamma = 0.5
delta = 2
h = cp.Variable(pos=True, name="h")
w = cp.Variable(pos=True, name="w")
d = cp.Variable(pos=True, name="d")
volume = h * w * d
wall_area = 2 * (h * w + h * d)
flr_area = w * d
hw_ratio = h/w
dw_ratio = d/w
constraints = [
wall_area <= A_wall,
flr_area <= A_flr,
hw_ratio >= alpha,
hw_ratio <= beta,
dw_ratio >= gamma,
dw_ratio <= delta
]
problem = cp.Problem(cp.Maximize(volume), constraints)
print(problem)
.. parsed-literal::
maximize h * w * d
subject to 2.0 * (h * w + h * d) <= 100.0
w * d <= 10.0
0.5 <= h / w
h / w <= 2.0
0.5 <= d / w
d / w <= 2.0
.. code:: python
assert not problem.is_dcp()
assert problem.is_dgp()
problem.solve(gp=True)
problem.value
.. parsed-literal::
77.45966630736292
.. code:: python
h.value
.. parsed-literal::
7.7459666715289766
.. code:: python
w.value
.. parsed-literal::
3.872983364643079
.. code:: python
d.value
.. parsed-literal::
2.581988871583608
.. code:: python
# A 1% increase in allowed wall space should yield approximately
# a 0.83% increase in maximum value.
constraints[0].dual_value
.. parsed-literal::
0.8333333206334043
.. code:: python
# A 1% increase in allowed wall space should yield approximately
# a 0.66% increase in maximum value.
constraints[1].dual_value
.. parsed-literal::
0.6666666801983365