I would like to start using Python for modelling and solving optimization problems. I would like to use both single-objective problems and multi-objective problems with a multidimensional objective space. For the multiobjective problems I'd like to use a metaheuristic, something like multiobjective evolutionary algorithms (like NSGA-2) for solving it.

Now my question is, which Python package for OR is suitable for doing this? Can I for example use something like:

• Pyomo
• Pulp
• Pyopt

I'd appreciate every comment and I'd be quite thankful for your help.

Update: Here is a more detailed desciption of what I intend to do. Basically I have a multiobjective optimization problem (mixed-integer linear program) with 2 objectives and I would like to compare three methods in different sceanrios with varying complexity:

1. Weighted sum approach solved by an exaxt algorithm (e.g. using a commerical solver like CPLEX)
2. Weightes sum approach solved by a single-objetice metaheuristic (like conventional evolutionary algorithms or particle swarm optimization)
3. Real multiobjectice optimization with a metaheuristic (like NSGA-2 or MOPSO)

I'd like to do this all in Python, as I read here in the forum that Python is strongly used in the OR community. Which packages would you advice me to use?

I would like to start using Python for modelling and solving optimization problems. I would like to use both single-objective problems and multi-objective problems with a multidimensional objective space. For the multiobjective problems I'd like to use a metaheuristic, something like multiobjective evolutionary algorithms (like NSGA-2) for solving it.

Now my question is, which Python package for OR is suitable for doing this? Can I for example use something like:

• Pyomo
• Pulp
• Pyopt

I'd appreciate every comment and I'd be quite thankful for your help.

Update: Here is a more detailed desciption of what I intend to do. Basically I have a multiobjective optimization problem (mixed-integer linear program) with 2 objectives and I would like to compare three methods in different sceanrios with varying complexity:

1. Weighted sum approach solved by an exaxt algorithm (e.g. using a commerical solver like CPLEX)
2. Weightes sum approach solved by a single-objetice metaheuristic (like conventional evolutionary algorithms or particle swarm optimization)
3. Real multiobjectice optimization with a metaheuristic (like NSGA-2 or MOPSO)

I'd like to do this all in Python, as I read here in the forum that Python is strongly used in the OR community. Which packages would you advice me to use?

Additional note: With real multiobjective optimization I mean, not to use a weighted sum approach (and thus convert the objective space into a one-dimensional space) but to have a multidimensional objective space and try to find the Pareto optimal solutions (e.g. with NSGA-2 which is a 'real' multiobjective optimization metaheuristic)

I would like to start using Python for modelling and solving optimization problems. I would like to use both single-objective problems and multi-objective problems with a multidimensional objective space. For the multiobjective problems I'd like to use a metaheuristic, something like multiobjective evolutionary algorithms (like NSGA-2) for solving it.

Now my question is, which Python package for OR is suitable for doing this? Can I for example use something like:

• Pyomo
• Pulp
• Pyopt

I'd appreciate every comment and I'd be quite thankful for your help.

I would like to start using Python for modelling and solving optimization problems. I would like to use both single-objective problems and multi-objective problems with a multidimensional objective space. For the multiobjective problems I'd like to use a metaheuristic, something like multiobjective evolutionary algorithms (like NSGA-2) for solving it.

Now my question is, which Python package for OR is suitable for doing this? Can I for example use something like:

• Pyomo
• Pulp
• Pyopt

I'd appreciate every comment and I'd be quite thankful for your help.

Update: Here is a more detailed desciption of what I intend to do. Basically I have a multiobjective optimization problem (mixed-integer linear program) with 2 objectives and I would like to compare three methods in different sceanrios with varying complexity:

1. Weighted sum approach solved by an exaxt algorithm (e.g. using a commerical solver like CPLEX)
2. Weightes sum approach solved by a single-objetice metaheuristic (like conventional evolutionary algorithms or particle swarm optimization)
3. Real multiobjectice optimization with a metaheuristic (like NSGA-2 or MOPSO)

I'd like to do this all in Python, as I read here in the forum that Python is strongly used in the OR community. Which packages would you advice me to use?

I would like to start using Pythong for modelling and solving optimization problems. I would like to use both single-objective problems and multi-objective problems with a multidimensional objetice space. For the multiobjective problems I'd like to use a metaheuristic something like multiobjective evolutionary algorithms (like NSGA-2) for solving it.

Now my question is, which Pythong package for OR is suitable for doing this? Can I for example use something like:

• Pyomo
• Pulp
• Pyopt

I'd appreciate every comment and I'd be quite thankful for your help.

I would like to start using Python for modelling and solving optimization problems. I would like to use both single-objective problems and multi-objective problems with a multidimensional objective space. For the multiobjective problems I'd like to use a metaheuristic, something like multiobjective evolutionary algorithms (like NSGA-2) for solving it.

Now my question is, which Python package for OR is suitable for doing this? Can I for example use something like:

• Pyomo
• Pulp
• Pyopt

I'd appreciate every comment and I'd be quite thankful for your help.