Optimization with proxy solver

This example demonstrates how to create and execute optimization using ParametricDesignStudyManager.

It creates an algorithm with ProxySolver node as a solver and then runs the created design study.

Perform required imports

Perform the required imports.

from math import sin
from pathlib import Path

import ansys.optislang.core.node_types as nt
from ansys.optislang.core.project_parametric import (
    Design,
    DesignVariable,
    ObjectiveCriterion,
    OptimizationParameter,
    Response,
)
from ansys.optislang.parametric.design_study import ParametricDesignStudyManager
from ansys.optislang.parametric.design_study_templates import (
    GeneralAlgorithmTemplate,
    ProxySolverNodeSettings,
)

Create template inputs

Define template inputs, that are used by the parametric design study manager to create and execute the design study.

project_path = Path().cwd() / "design_manager_example.opf"
parameters = [
    OptimizationParameter(name=f"X{i}", reference_value=0.0, range=(-3.14, 3.14))
    for i in range(1, 6)
]
responses = [Response(name="Y", reference_value=0.0)]
criteria = [ObjectiveCriterion("minY", expression="Y")]


def callback(designs: list[Design]) -> list[Design]:
    """Calculate coupled function for provided designs."""
    results_designs = []
    for design in designs:
        X1 = design.parameters[design.parameters_names.index("X1")].value
        X2 = design.parameters[design.parameters_names.index("X2")].value
        X3 = design.parameters[design.parameters_names.index("X3")].value
        X4 = design.parameters[design.parameters_names.index("X4")].value
        X5 = design.parameters[design.parameters_names.index("X5")].value

        Y = 0.5 * X1 + X2 + 0.5 * X1 * X2 + 5 * sin(X3) + 0.2 * X4 + 0.1 * X5
        id = design.id

        # create instance of design with new values
        output_design = Design(
            responses=[DesignVariable("Y", Y)],
            design_id=id,
        )
        results_designs.append(output_design)
    return results_designs


solver_settings = ProxySolverNodeSettings(callback=callback, multi_design_launch_num=-1)

Create NLPQLP template

Define template that will be transformed into a NLPQLP system with proxy solver.

nlpqlp_template = GeneralAlgorithmTemplate(
    parameters=parameters,
    criteria=criteria,
    responses=responses,
    algorithm_type=nt.NLPQLP,
    solver_type=nt.ProxySolver,
    solver_settings=solver_settings,
)

Create NLPQLP system

Instantiate parametric design study manager, create and execute the design study.

design_study_manager = ParametricDesignStudyManager(project_path=project_path)
study = design_study_manager.create_design_study(template=nlpqlp_template)
study.execute()
design_study_manager.save()

Stop and cancel project

Stop and cancel the project.

design_study_manager.optislang.dispose()

View generated workflow

This image shows the generated workflow.