Solver

Configure and run the solver to find optimal solutions.

Tags:

The solver is the engine that finds optimal solutions to your planning problems. This section covers how to configure and run it.

Topics

Configuration - SolverConfig, TerminationConfig, and other settings
Running the Solver - Synchronous solving with Solver.solve()
Solver Manager - Asynchronous and concurrent solving
Solution Manager - Analyze and explain solutions
Benchmarking - Compare configurations and tune performance

Quick Example

from solverforge_legacy.solver import SolverFactory
from solverforge_legacy.solver.config import (
    SolverConfig, ScoreDirectorFactoryConfig, TerminationConfig, Duration
)

# Configure the solver
solver_config = SolverConfig(
    solution_class=Timetable,
    entity_class_list=[Lesson],
    score_director_factory_config=ScoreDirectorFactoryConfig(
        constraint_provider_function=define_constraints
    ),
    termination_config=TerminationConfig(
        spent_limit=Duration(seconds=30)
    )
)

# Create and run the solver
solver_factory = SolverFactory.create(solver_config)
solver = solver_factory.build_solver()

problem = load_problem()  # Your problem data
solution = solver.solve(problem)

print(f"Best score: {solution.score}")

Termination

The solver needs to know when to stop. Common termination conditions:

Condition	Description
`spent_limit`	Stop after a time limit (e.g., 30 seconds)
`best_score_limit`	Stop when a target score is reached
`unimproved_spent_limit`	Stop if no improvement for a duration
`step_count_limit`	Stop after a number of optimization steps