Running Optimization

This guide shows how to run an optimization scenario with ws3.

Prerequisites

A loaded ForestModel
Understanding of linear programming concepts

Procedure

1. Load the model

from ws3.forest import ForestModel

fm = ForestModel(
    model_name="my_model",
    model_path="path/to/model",
    base_year=2020,
    horizon=10,
    period_length=10
)
fm.import_areas_section()
fm.import_yields_section()
fm.import_actions_section()
fm.import_transitions_section()
fm.initialize_areas()
fm.add_null_action()
fm.reset_actions()

2. Create a Problem

from ws3.opt import Problem

problem = Problem(
    name="base_scenario",
    sense=1,  # SENSE_MAXIMIZE
    solver="highs"
)

3. Define the objective

coeffs = {var_name: 1.0 for var_name in problem.var_names()}
problem.z(coeffs)

4. Add constraints

problem.add_constraint(
    name="even_flow",
    coeffs={var_name: 1.0 if "period_0" in var_name else -1.2
            for var_name in problem.var_names()},
    sense="<=",
    rhs=0.0
)

5. Solve

problem.solve(verbose=True)

6. Inspect results

solution = problem.solution()
print(f"Objective value: {problem.z()}")
print(f"Variables: {len(solution)}")

Troubleshooting

Solver fails to converge — verify all development types and actions are defined and constraint ranges are feasible.
No harvest in schedule — check that actions are applicable to development types and that area constraints allow harvest.
Solver takes too long — reduce the planning horizon or simplify constraints.