Using NumPy arrays to create variables
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Type: | Programming |
Rating: | 2 (easy-medium) |
Description: | Use NumPy arrays for creating a 3-dimensional array of variables, then use it to create a model. |
File(s): | example_array.py |
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example_array.py |
#!/bin/env python # # Use NumPy arrays for creating a 3-dimensional array of variables, # then use it to create a mode. # from __future__ import print_function import numpy as np import xpress as xp S1 = range(2) S2 = range(3) S3 = range(4) m = xp.problem() h = np.array([[[xp.var(vartype=xp.binary) for i in S1] for j in S2] for k in S3]) m.addVariable(h) m.setObjective(h[0][0][0] * h[0][0][0] + h[1][0][0] * h[0][0][0] + h[1][0][0] * h[1][0][0] + xp.Sum(h[i][j][k] for i in S3 for j in S2 for k in S1)) cons00 = - h[0][0][0] * h[0][0][0] + \ xp.Sum(i * j * k * h[i][j][k] for i in S3 for j in S2 for k in S1) >= 11 m.addConstraint(cons00) m.solve() # Get the matrix representation of the quadratic part of the single # constraint mstart1 = [] mclind1 = [] dqe1 = [] m.getqrowqmatrix(cons00, mstart1, mclind1, dqe1, 29, h[0][0][0], h[3][2][1]) print("row 0:", mstart1, mclind1, dqe1) |
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