pub struct PrimalDual<'a> {
graph: &'a BidirectionalSparseGraph,
capacities: Vec<u64>,
costs: Vec<i64>,
potential: Vec<i64>,
dist: Vec<i64>,
prev_vertex: Vec<usize>,
prev_edge: Vec<usize>,
has_negedge: bool,
queue: BinaryHeap<(Reverse<i64>, usize)>,
}Fields§
§graph: &'a BidirectionalSparseGraph§capacities: Vec<u64>§costs: Vec<i64>§potential: Vec<i64>§dist: Vec<i64>§prev_vertex: Vec<usize>§prev_edge: Vec<usize>§has_negedge: bool§queue: BinaryHeap<(Reverse<i64>, usize)>Implementations§
Source§impl PrimalDual<'_>
impl PrimalDual<'_>
pub fn builder(vsize: usize, esize_expect: usize) -> PrimalDualBuilder
Sourcefn bellman_ford(&mut self, s: usize)
fn bellman_ford(&mut self, s: usize)
Examples found in repository?
crates/competitive/src/graph/minimum_cost_flow.rs (line 140)
136 pub fn minimum_cost_flow_limited(&mut self, s: usize, t: usize, limit: u64) -> (u64, i64) {
137 let mut flow = 0;
138 let mut cost = 0;
139 if self.has_negedge {
140 self.bellman_ford(s);
141 }
142 while flow < limit && self.dijkstra(s, t) {
143 let shortest = self.dist[t];
144 for (p, d) in self.potential.iter_mut().zip(self.dist.iter()) {
145 *p = p.saturating_add((*d).min(shortest));
146 }
147 let mut f = limit - flow;
148 let mut v = t;
149 while v != s {
150 f = f.min(self.capacities[self.prev_edge[v]]);
151 v = self.prev_vertex[v];
152 }
153 flow += f;
154 cost += f as i64 * (self.potential[t] - self.potential[s]);
155 let mut v = t;
156 while v != s {
157 self.capacities[self.prev_edge[v]] -= f;
158 self.capacities[self.prev_edge[v] ^ 1] += f;
159 v = self.prev_vertex[v];
160 }
161 }
162 (flow, cost)
163 }Sourcefn dijkstra(&mut self, s: usize, t: usize) -> bool
fn dijkstra(&mut self, s: usize, t: usize) -> bool
Examples found in repository?
crates/competitive/src/graph/minimum_cost_flow.rs (line 142)
136 pub fn minimum_cost_flow_limited(&mut self, s: usize, t: usize, limit: u64) -> (u64, i64) {
137 let mut flow = 0;
138 let mut cost = 0;
139 if self.has_negedge {
140 self.bellman_ford(s);
141 }
142 while flow < limit && self.dijkstra(s, t) {
143 let shortest = self.dist[t];
144 for (p, d) in self.potential.iter_mut().zip(self.dist.iter()) {
145 *p = p.saturating_add((*d).min(shortest));
146 }
147 let mut f = limit - flow;
148 let mut v = t;
149 while v != s {
150 f = f.min(self.capacities[self.prev_edge[v]]);
151 v = self.prev_vertex[v];
152 }
153 flow += f;
154 cost += f as i64 * (self.potential[t] - self.potential[s]);
155 let mut v = t;
156 while v != s {
157 self.capacities[self.prev_edge[v]] -= f;
158 self.capacities[self.prev_edge[v] ^ 1] += f;
159 v = self.prev_vertex[v];
160 }
161 }
162 (flow, cost)
163 }Sourcepub fn minimum_cost_flow_limited(
&mut self,
s: usize,
t: usize,
limit: u64,
) -> (u64, i64)
pub fn minimum_cost_flow_limited( &mut self, s: usize, t: usize, limit: u64, ) -> (u64, i64)
Return (flow, cost).
Examples found in repository?
More examples
pub fn get_flow(&self, eid: usize) -> u64
Trait Implementations§
Auto Trait Implementations§
impl<'a> Freeze for PrimalDual<'a>
impl<'a> RefUnwindSafe for PrimalDual<'a>
impl<'a> Send for PrimalDual<'a>
impl<'a> Sync for PrimalDual<'a>
impl<'a> Unpin for PrimalDual<'a>
impl<'a> UnsafeUnpin for PrimalDual<'a>
impl<'a> UnwindSafe for PrimalDual<'a>
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more