use super::*;
use crate::construction::heuristics::InsertionContext;
use crate::solver::search::*;
use crate::solver::RefinementContext;
use std::cell::RefCell;
pub struct NeighbourRemoval {
limits: RemovalLimits,
}
impl NeighbourRemoval {
pub fn new(limits: RemovalLimits) -> Self {
Self { limits }
}
}
impl Ruin for NeighbourRemoval {
fn run(&self, _: &RefinementContext, mut insertion_ctx: InsertionContext) -> InsertionContext {
let problem = insertion_ctx.problem.clone();
let random = insertion_ctx.environment.random.clone();
let tracker = RefCell::new(JobRemovalTracker::new(&self.limits, random.as_ref()));
let mut tabu_list = TabuList::from(&insertion_ctx);
let init_seed =
select_seed_job_with_tabu_list(&insertion_ctx, &tabu_list).map(|(profile, _, job)| (profile, job));
select_neighbors(&problem, init_seed).take_while(|_| !tracker.borrow().is_limit()).for_each(|job| {
let route_idx =
insertion_ctx.solution.routes.iter().position(|route_ctx| route_ctx.route().tour.contains(&job));
if let Some(route_idx) = route_idx {
if tracker.borrow_mut().try_remove_job(&mut insertion_ctx.solution, route_idx, &job) {
tabu_list.add_job(job);
tabu_list.add_actor(insertion_ctx.solution.routes[route_idx].route().actor.clone());
}
}
});
tabu_list.inject(&mut insertion_ctx);
insertion_ctx
}
}