#!/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} that ranges in Python are from to>= 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 ())