Python Pulp does not add all variables constraints and forgets objective function -


i running in problems using module pulp. want create mixed integer linear programming problem , write lp file. after solve cplex.

the problem when add second constraints, objective function becomes false(dummy added) , first constraint added decision variable x.

this code: hope can me out!

bay_model = pulp.lpproblem('bay problem', pulp.lpminimize)  y = pulp.lpvariable.dicts(name = "y",indexs = (flight, flight, gates),                           lowbound = 0, upbound = 1,cat = pulp.lpinteger)  x = pulp.lpvariable.dicts(name = "x",indexs = (flight,gates),lowbound = 0,                                                        upbound = 1, cat=pulp.lpinteger)     bay_model += pulp.lpsum([x[i][j]*g.distance[j] in flight j in gates])  in flight:      bay_model += pulp.lpsum([x[i][j] j in gates]) == 1      print "flight must assigned" + str(i)  k in gates:      bay_model += [y[i][j][k] * f.time_matrix[i][j] in flight j in flight if f.time_matrix[i][j] == 1] <= g.capacity[k]      bay_model += [(2 * y[i][j][k] - x[i][k] - x[j][k]) in flight j in flight] == 0      print "time constraint" + str(k)

i don't think list comprehensions [x[i] in ...] can added bay_model this. if want constraint hold on each element in list can define elements beforehand:

for in flights:   j in flights:     if f.time_matrix[i][j] == 1:       k in gates:         bay_model += y[i][j][k] * f.time_matrix[i][j] <= g.capacity[k]

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