CODEWITHSUNDEEP
python-2.7constraintssparse-matrixcplex
steph
steph

Reputation: 565

Set up model in CPLEX using Python API

In fact, I'm trying to implement the very simple model formulation:

min  sum_i(y_i*f_i) + sum_i(sum_j(x_ij*c_ij))
s.t.   sum_i(x_ij) = 1         for all j
             x_ij <= y_i       for all i,j
         x_ij, y_i are binary

But I simply cannot figure out how the Python API works. They suggest creating variables like this:

model.variables.add(obj = fixedcost, 
                    lb = [0] * num_facilities, 
                    ub = [1] * num_facilities, 
                    types = ["B"] * num_facilities)

# Create one binary variable for each facility/client pair. The variables
# model whether a client is served by a facility.
for c in range(num_clients):
    model.variables.add(obj = cost[c], 
                        lb = [0] * num_facilities, 
                        ub = [1] * num_facilities, 
                        types = ["B"] * num_facilities)

# Create corresponding indices for later use
supply = []
for c in range(num_clients):
    supply.append([])
    for f in range(num_facilities):
        supply[c].append((c+1)*(num_facilities)+f)

# Constraint no. 1:
for c in range(num_clients):        
    assignment_constraint = cplex.SparsePair(ind = [supply[c][f] for f in \
                                                    range(num_facilities)],
                                             val = [1] * num_facilities)
    model.linear_constraints.add(lin_expr = [assignment_constraint],                    
                                 senses = ["L"], 
                                 rhs = [1])

For this constraints I have no idea how the variables from above are refered to since it only mentions an auxiliary list of lists. Can anyone explain to me how that should work? The problem is easy, I also know how to do it in C++ but the Python API is a closed book to me.

The problem is the uncapacitated facility location problem and I want to adapt the example file facility.py

EDIT: One idea for constraint no.2 is to create one-dimensional vectors and use vector addition to create the final constraint. But that tells me that this is an unsupported operand for SparsePairs

for f in range(num_facilities):
    index = [f]
    value = [-1.0]
    for c in range(num_clients):
        open_constraint = cplex.SparsePair(ind = index, val = value) + cplex.SparsePair(ind = [supply[c][f]], val = [1.0])
        model.linear_constraints.add(lin_expr=[open_constraint],
                                    senses = ["L"],
                                    rhs = [0])

Upvotes: 0

Views: 1320

Answers (1)

rkersh
rkersh

Reputation: 4465

The Python API is closer to the C Callable Library in nature than the C++/Concert API. Variables are indexed from 0 to model.variables.get_num() - 1 and can be referred to by index, for example, when creating constraints. They can also be referred to by name (the add method has an optional names argument). See the documentation for the VariablesInterface here (this is for version 12.5.1, which I believe you are using, given your previous post).

It may help to start looking at the most simple examples like lpex1.py (and read the comments). Finally, I highly recommend playing with the Python API from the interactive Python prompt (aka the REPL). You can read the help there and type things in to see what they do.

You also might want to take a look at the docplex package. This is a modeling layer built on top of the CPLEX Python API (or which can solve on the cloud if you don't have a local installation of CPLEX installed).

Upvotes: 1

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