#!/bin/env python
#
# Demonstrate how variables, or arrays thereof, and constraints, or
# arrays of constraints, can be added into a problem. Prints the
# solution and all attributes/controls of the problem.
#
from __future__ import print_function
import xpress as xp
N = 4
S = range (N)
v = [xp.var (name = "y{0}".format (i)) for i in S] # set name of a variable as
m = xp.problem ()
v1 = xp.var (name = "v1", lb=0, ub=10, threshold=5, vartype = xp.continuous)
v2 = xp.var (name = "v2", lb=1, ub=7, threshold=3, vartype = xp.continuous)
vb = xp.var (name = "vb", vartype = xp.binary)
v = [xp.var (name = "y{0}".format (i), lb = 0, ub = 2*N) for i in S] # set name of a variable as
m.addVariable (vb, v, v1, v2) # adds both v, a vector (list) of variables, and v1 and v2, two scalar variables.
c1 = v1 + v2 >= 5
m.addConstraint (c1, # Adds a list of constraints: three single constraints...
2*v1 + 3*v2 >= 5,
v[0] + v[2] >= 1,
# ... and a set of constraints indexed by all {i in
# S: i<N-1} (recall that ranges in Python are from 0
# to n-1)
(v[i+1] >= v[i] + 1 for i in S if i < N-1))
m.setObjective (xp.Sum ([i*v[i] for i in S]), sense = xp.minimize) # objective overwritten at each setObjective ()
m.solve ()
print ("status: ", m.getProbStatus ())
print ("string: ", m.getProbStatusString ())
print ("solution:", m.getSolution ())
print ("Attributes: ----------------------------------------")
print (m.getAttrib ())
print ("Controls: -------------------------------------------")
print (m.getControl ())
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