text: from itertools import product
  from mip import Model, BINARY
  
  n = m = 3
  
  times = [[2, 1, 2],
           [1, 2, 2],
           [1, 2, 1]]
  
  M = sum(times[i][j] for i in range(n) for j in range(m))
  
  machines = [[2, 0, 1],
              [1, 2, 0],
              [2, 1, 0]]
  
  model = Model('JSSP')
  
  c = model.add_var(name="C")
  x = [[model.add_var(name='x({},{})'.format(j+1, i+1))
        for i in range(m)] for j in range(n)]
  y = [[[model.add_var(var_type=BINARY, name='y({},{},{})'.format(j+1, k+1, i+1))
         for i in range(m)] for k in range(n)] for j in range(n)]
  
  model.objective = c
  
  for (j, i) in product(range(n), range(1, m)):
      model += x[j][machines[j][i]] - x[j][machines[j][i-1]] >= \
          times[j][machines[j][i-1]]
  
  for (j, k) in product(range(n), range(n)):
      if k != j:
          for i in range(m):
              model += x[j][i] - x[k][i] + M*y[j][k][i] >= times[k][i]
              model += -x[j][i] + x[k][i] - M*y[j][k][i] >= times[j][i] - M
  
  for j in range(n):
      model += c - x[j][machines[j][m - 1]] >= times[j][machines[j][m - 1]]
  
  model.optimize()
  
  print("Completion time: ", c.x)
  for (j, i) in product(range(n), range(m)):
      print("task %d starts on machine %d at time %g " % (j+1, i+1, x[j][i].x))
  