Hi,

doopl helps call OPL CPLEX from python https://www.linkedin.com/feed/update/urn:li:activity:6450620726520139776

Let me give you a tiny example out of https://www.linkedin.com/pulse/what-optimization-how-can-help-you-do-more-less-zoo-buses-fleischer/

 

You may write zootupleset.mod

int nbKids=300;

// a tuple is like a struct in C, a class in C++ or a record in Pascal
tuple bus
{
key int nbSeats;
float cost;
}

// This is a tuple set
{bus} buses=...;

// asserts help make sure data is fine
assert forall(b in buses) b.nbSeats>0;
assert forall(b in buses) b.cost>0;

// decision variable array
dvar int+ nbBus[buses];

// objective
minimize
 sum(b in buses) b.cost*nbBus[b];
 
// constraints
subject to
{
 sum(b in buses) b.nbSeats*nbBus[b]>=nbKids;
}

tuple solution
{
  int nbBus;
  int sizeBus;
}

{solution} solutions={<nbBus[b],b.nbSeats> | b in buses};

 

and then the following python code

from doopl.factory import *

# Data

Buses=[
    (40,500),
    (30,400)
    ]

# Create an OPL model from a .mod file
with create_opl_model(model="zootupleset.mod") as opl:
    # tuple can be a list of tuples, a pandas dataframe...
    opl.set_input("buses", Buses)

    # Generate the problem and solve it.
    opl.run()

    # Get the names of post processing tables
    print("Table names are: "+ str(opl.output_table_names))

    # Get all the post processing tables as dataframes.
    for name, table in iteritems(opl.report):
        print("Table : " + name)
        for t in table.itertuples(index=False):
            print(t)

        # nicer display
        for t in table.itertuples(index=False):
            print(t[0]," buses ",t[1], "seats")

 

gives

 

Table names are: ['solutions']
Table : solutions
Pandas(nbBus=6, sizeBus=40)
Pandas(nbBus=2, sizeBus=30)
6  buses  40 seats
2  buses  30 seats

regards

 

NB:

You may download doopl at https://pypi.org/project/doopl/

You may also translate OPL to Python https://www.ibm.com/developerworks/community/forums/html/topic?id=a8580237-639a-411b-b1df-f390a24da06c&ps=25

 

 

 

 

 

 

#DecisionOptimization
#OPLusingCPLEXOptimizer

Originally posted by: qtbgo

Can we setObjCoef in doopl?

#DecisionOptimization
#OPLusingCPLEXOptimizer

Hi,

you cannot yet call setObjCoef in doopl and do not hesitate to log a wish in Aha if you need that

https://ibm-data-and-ai.ideas.aha.io/?project=CPLEX

But what you can do is use a main in OPL and call that from doopl.

Let me show you.

zootupleset.mod

int nbKids=300;

    // a tuple is like a struct in C, a class in C++ or a record in Pascal
    tuple bus
    {
    key int nbSeats;
    float cost;
    }

    // This is a tuple set
    {bus} buses=...; //{<40,500>,<30,400>};

    // asserts help make sure data is fine
    assert forall(b in buses) b.nbSeats>0;
    assert forall(b in buses) b.cost>0;

    // decision variable array
    dvar int+ nbBus[buses];

    // objective
    minimize
     sum(b in buses) b.cost*nbBus[b];
     
    // constraints
    subject to
    {
     sum(b in buses) b.nbSeats*nbBus[b]>=nbKids;
    }

    tuple solution
    {
      int nbBus;
      int sizeBus;
    }

    {solution} solutions={<nbBus[b],b.nbSeats> | b in buses};
    
    main
    {
    thisOplModel.generate();
    cplex.solve();
    var b1=Opl.first(thisOplModel.buses);
    cplex.setObjCoef(thisOplModel.nbBus[b1], 200);
    cplex.solve();
    thisOplModel.postProcess();    
    }

 

and then the following python code

from doopl.factory import *

# Data

Buses=[
    (40,500),
    (30,400)
    ]

# Create an OPL model from a .mod file
with create_opl_model(model="zootupleset.mod") as opl:
    # tuple can be a list of tuples, a pandas dataframe...
    opl.set_input("buses", Buses)

    # Generate the problem and solve it.
    opl.run()

    # Get the names of post processing tables
    print("Table names are: "+ str(opl.output_table_names))

    # Get all the post processing tables as dataframes.
    for name, table in iteritems(opl.report):
        print("Table : " + name)
        for t in table.itertuples(index=False):
            print(t)

        # nicer display
        for t in table.itertuples(index=False):
            print(t[0]," buses ",t[1], "seats")

will give

 

8  buses  40 seats
0  buses  30 seats

regards

 

#DecisionOptimization
#OPLusingCPLEXOptimizer