Struct vrp_core::solver::Solver

pub struct Solver { /* private fields */ }

Solves a Vehicle Routing Problem and returns a (solution, its cost) pair in case of success or error description, if solution cannot be found.

Implementations

impl Solver

pub fn new( problem: Arc<Problem>, config: EvolutionConfig<RefinementContext, GoalContext, InsertionContext>, ) -> Self

Tries to create an instance of Solver from provided config.

Examples found in repository

examples/custom_objective.rs (line 146)

fn main() -> GenericResult<()> {
    let transport = Arc::new(define_routing_data()?);

    let goal = define_goal(transport.clone())?;
    let problem = Arc::new(define_problem(goal, transport)?);

    let config = VrpConfigBuilder::new(problem.clone()).prebuild()?.with_max_generations(Some(10)).build()?;

    // run the VRP solver and get the best known solution
    let solution = Solver::new(problem, config).solve()?;

    assert_eq!(solution.unassigned.len(), 2, "expected two assigned jobs due to capacity constraint");
    assert_eq!(solution.routes.len(), 1, "only one tour should be there");
    assert_eq!(
        solution.get_locations().map(Iterator::collect::<Vec<_>>).collect::<Vec<_>>(),
        vec![vec![0, 2, 4]],
        "tour doesn't serve only top-prio jobs"
    );
    assert_eq!(solution.cost, 545., "unexpected cost - closest to depot jobs should be assigned");

    Ok(())
}

examples/custom_constraint.rs (line 129)

fn main() -> GenericResult<()> {
    let transport = Arc::new(define_routing_data()?);

    let goal = define_goal(transport.clone())?;
    let problem = Arc::new(define_problem(goal, transport)?);

    let config = VrpConfigBuilder::new(problem.clone()).prebuild()?.with_max_generations(Some(10)).build()?;

    // run the VRP solver and get the best known solution
    let solution = Solver::new(problem, config).solve()?;

    assert_eq!(
        solution.unassigned.len(),
        2,
        "expected two assigned jobs due to hardware requirement and capacity constraints"
    );
    assert_eq!(solution.routes.len(), 1, "only one tour should be there: second vehicle cannot serve hardware jobs");
    assert_eq!(solution.cost, 1050., "unexpected cost - closest to depot jobs should be assigned");

    // simple way to explore the solution, more advanced are available too
    println!(
        "\nIn solution, locations are visited in the following order:\n{:?}\n",
        solution.get_locations().map(Iterator::collect::<Vec<_>>).collect::<Vec<_>>()
    );

    Ok(())
}

examples/cvrp.rs (line 94)

fn main() -> GenericResult<()> {
    // get routing data, see `./common/routing.rs` for details
    let transport = Arc::new(define_routing_data()?);

    // specify CVRP variant as problem definition and the goal of optimization
    let goal = define_goal(transport.clone())?;
    let problem = Arc::new(define_problem(goal, transport)?);

    // build a solver config with the predefined settings to run 5 secs or 10 generations at most
    let config = VrpConfigBuilder::new(problem.clone())
        .prebuild()?
        .with_max_time(Some(5))
        .with_max_generations(Some(10))
        .build()?;

    // run the VRP solver and get the best known solution
    let solution = Solver::new(problem, config).solve()?;

    assert!(solution.unassigned.is_empty(), "has unassigned jobs, but all jobs must be assigned");
    assert_eq!(solution.routes.len(), 2, "two tours are expected");
    assert_eq!(solution.cost, 2135., "unexpected cost (total distance traveled)");

    // simple way to explore the solution, more advanced are available too
    println!(
        "\nIn solution, locations are visited in the following order:\n{:?}\n",
        solution.get_locations().map(Iterator::collect::<Vec<_>>).collect::<Vec<_>>()
    );

    Ok(())
}

examples/pdptw.rs (line 105)

fn main() -> GenericResult<()> {
    // get routing data, see `./common/routing.rs` for details
    let transport = Arc::new(define_routing_data()?);

    // specify PDPTW variant as problem definition and the goal of optimization
    let goal = define_goal(transport.clone())?;
    let problem = Arc::new(define_problem(goal, transport)?);

    // build a solver config with the predefined settings to run 5 secs or 10 generations at most
    let config = VrpConfigBuilder::new(problem.clone())
        .prebuild()?
        .with_max_time(Some(5))
        .with_max_generations(Some(10))
        .build()?;

    // run the VRP solver and get the best known solution
    let solution = Solver::new(problem, config).solve()?;

    assert!(solution.unassigned.is_empty(), "has unassigned jobs, but all jobs must be assigned");
    assert_eq!(solution.routes.len(), 1, "one tour should be there");
    assert_eq!(solution.cost, 1105., "unexpected cost (total distance traveled)");

    // simple way to explore the solution, more advanced are available too
    println!(
        "\nIn solution, locations are visited in the following order:\n{:?}\n",
        solution.get_locations().map(Iterator::collect::<Vec<_>>).collect::<Vec<_>>()
    );

    Ok(())
}

pub fn solve(self) -> GenericResult<Solution>

Solves a Vehicle Routing Problem and returns a feasible solution in case of success or error description if solution cannot be found.

Examples found in repository

examples/custom_objective.rs (line 146)

fn main() -> GenericResult<()> {
    let transport = Arc::new(define_routing_data()?);

    let goal = define_goal(transport.clone())?;
    let problem = Arc::new(define_problem(goal, transport)?);

    let config = VrpConfigBuilder::new(problem.clone()).prebuild()?.with_max_generations(Some(10)).build()?;

    // run the VRP solver and get the best known solution
    let solution = Solver::new(problem, config).solve()?;

    assert_eq!(solution.unassigned.len(), 2, "expected two assigned jobs due to capacity constraint");
    assert_eq!(solution.routes.len(), 1, "only one tour should be there");
    assert_eq!(
        solution.get_locations().map(Iterator::collect::<Vec<_>>).collect::<Vec<_>>(),
        vec![vec![0, 2, 4]],
        "tour doesn't serve only top-prio jobs"
    );
    assert_eq!(solution.cost, 545., "unexpected cost - closest to depot jobs should be assigned");

    Ok(())
}

examples/custom_constraint.rs (line 129)

fn main() -> GenericResult<()> {
    let transport = Arc::new(define_routing_data()?);

    let goal = define_goal(transport.clone())?;
    let problem = Arc::new(define_problem(goal, transport)?);

    let config = VrpConfigBuilder::new(problem.clone()).prebuild()?.with_max_generations(Some(10)).build()?;

    // run the VRP solver and get the best known solution
    let solution = Solver::new(problem, config).solve()?;

    assert_eq!(
        solution.unassigned.len(),
        2,
        "expected two assigned jobs due to hardware requirement and capacity constraints"
    );
    assert_eq!(solution.routes.len(), 1, "only one tour should be there: second vehicle cannot serve hardware jobs");
    assert_eq!(solution.cost, 1050., "unexpected cost - closest to depot jobs should be assigned");

    // simple way to explore the solution, more advanced are available too
    println!(
        "\nIn solution, locations are visited in the following order:\n{:?}\n",
        solution.get_locations().map(Iterator::collect::<Vec<_>>).collect::<Vec<_>>()
    );

    Ok(())
}

examples/cvrp.rs (line 94)

fn main() -> GenericResult<()> {
    // get routing data, see `./common/routing.rs` for details
    let transport = Arc::new(define_routing_data()?);

    // specify CVRP variant as problem definition and the goal of optimization
    let goal = define_goal(transport.clone())?;
    let problem = Arc::new(define_problem(goal, transport)?);

    // build a solver config with the predefined settings to run 5 secs or 10 generations at most
    let config = VrpConfigBuilder::new(problem.clone())
        .prebuild()?
        .with_max_time(Some(5))
        .with_max_generations(Some(10))
        .build()?;

    // run the VRP solver and get the best known solution
    let solution = Solver::new(problem, config).solve()?;

    assert!(solution.unassigned.is_empty(), "has unassigned jobs, but all jobs must be assigned");
    assert_eq!(solution.routes.len(), 2, "two tours are expected");
    assert_eq!(solution.cost, 2135., "unexpected cost (total distance traveled)");

    // simple way to explore the solution, more advanced are available too
    println!(
        "\nIn solution, locations are visited in the following order:\n{:?}\n",
        solution.get_locations().map(Iterator::collect::<Vec<_>>).collect::<Vec<_>>()
    );

    Ok(())
}

examples/pdptw.rs (line 105)

fn main() -> GenericResult<()> {
    // get routing data, see `./common/routing.rs` for details
    let transport = Arc::new(define_routing_data()?);

    // specify PDPTW variant as problem definition and the goal of optimization
    let goal = define_goal(transport.clone())?;
    let problem = Arc::new(define_problem(goal, transport)?);

    // build a solver config with the predefined settings to run 5 secs or 10 generations at most
    let config = VrpConfigBuilder::new(problem.clone())
        .prebuild()?
        .with_max_time(Some(5))
        .with_max_generations(Some(10))
        .build()?;

    // run the VRP solver and get the best known solution
    let solution = Solver::new(problem, config).solve()?;

    assert!(solution.unassigned.is_empty(), "has unassigned jobs, but all jobs must be assigned");
    assert_eq!(solution.routes.len(), 1, "one tour should be there");
    assert_eq!(solution.cost, 1105., "unexpected cost (total distance traveled)");

    // simple way to explore the solution, more advanced are available too
    println!(
        "\nIn solution, locations are visited in the following order:\n{:?}\n",
        solution.get_locations().map(Iterator::collect::<Vec<_>>).collect::<Vec<_>>()
    );

    Ok(())
}