Find a path from s to t using as few red nodes as possible Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern) Announcing the arrival of Valued Associate #679: Cesar Manara Unicorn Meta Zoo #1: Why another podcast?Find a path passing through the minimum number of odd nodesDijkstra algorithm vs breadth first search for shortest path in graphAlgorithm to find diameter of a tree using BFS/DFS. Why does it work?Finding shortest path from a node to any node of a particular typeParallel algorithm to find if a set of nodes is on an elememtry cycle in a directed/undirected graphShortest path in unweighted graph using an iterator onlyShortest Path using DFS on weighted graphsCan a 3 Color DFS be used to identify cycles (not just detect them)?Find a path that contains specific nodes without back and forward edgesChecking if there is a single path that visits all nodes in a directed graphFind shortest path that goes through at least 5 red edges
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Find a path from s to t using as few red nodes as possible
Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern)
Announcing the arrival of Valued Associate #679: Cesar Manara
Unicorn Meta Zoo #1: Why another podcast?Find a path passing through the minimum number of odd nodesDijkstra algorithm vs breadth first search for shortest path in graphAlgorithm to find diameter of a tree using BFS/DFS. Why does it work?Finding shortest path from a node to any node of a particular typeParallel algorithm to find if a set of nodes is on an elememtry cycle in a directed/undirected graphShortest path in unweighted graph using an iterator onlyShortest Path using DFS on weighted graphsCan a 3 Color DFS be used to identify cycles (not just detect them)?Find a path that contains specific nodes without back and forward edgesChecking if there is a single path that visits all nodes in a directed graphFind shortest path that goes through at least 5 red edges
$begingroup$
Was doing a little interview prep. Given an undirected graph G, such that each node is colored red or blue and |E|≥|V|, find a path in O(|E|) time such that starting and ending at 2 blue nodes, s and t, that you pass through as few red nodes as possible.
Initial Impressions: Since |E|≥|V|, O(|E|) time would include O(|E|+|V|), which means the solution likely uses BFS or DFS. Modifying the graph such that causing the all red nodes must be forced down a directed path of some long length (after making the whole graph directed) in order to use out-of-the-box BFS seems not viable, as it would mean constructing a new graph would be along O(|E||V|) time.
Another method I toyed around with was propagating values to nodes based on the safest path to that node while doing a DFS search, but not all values were guaranteed to update.
I still want to try to solve this myself, but I'm really stuck right now. Was wondering if there were any hints I could get. There are much simpler ways of doing this if it weren't for the O(|E|) time. Djikstras with creating some edge weights would work, but wouldn't be within the time bound.
graphs
$endgroup$
add a comment |
$begingroup$
Was doing a little interview prep. Given an undirected graph G, such that each node is colored red or blue and |E|≥|V|, find a path in O(|E|) time such that starting and ending at 2 blue nodes, s and t, that you pass through as few red nodes as possible.
Initial Impressions: Since |E|≥|V|, O(|E|) time would include O(|E|+|V|), which means the solution likely uses BFS or DFS. Modifying the graph such that causing the all red nodes must be forced down a directed path of some long length (after making the whole graph directed) in order to use out-of-the-box BFS seems not viable, as it would mean constructing a new graph would be along O(|E||V|) time.
Another method I toyed around with was propagating values to nodes based on the safest path to that node while doing a DFS search, but not all values were guaranteed to update.
I still want to try to solve this myself, but I'm really stuck right now. Was wondering if there were any hints I could get. There are much simpler ways of doing this if it weren't for the O(|E|) time. Djikstras with creating some edge weights would work, but wouldn't be within the time bound.
graphs
$endgroup$
1
$begingroup$
Try a variant of BFS in which you first find all red nodes reachable only via blue nodes, and so on.
$endgroup$
– Yuval Filmus
Apr 1 at 20:22
add a comment |
$begingroup$
Was doing a little interview prep. Given an undirected graph G, such that each node is colored red or blue and |E|≥|V|, find a path in O(|E|) time such that starting and ending at 2 blue nodes, s and t, that you pass through as few red nodes as possible.
Initial Impressions: Since |E|≥|V|, O(|E|) time would include O(|E|+|V|), which means the solution likely uses BFS or DFS. Modifying the graph such that causing the all red nodes must be forced down a directed path of some long length (after making the whole graph directed) in order to use out-of-the-box BFS seems not viable, as it would mean constructing a new graph would be along O(|E||V|) time.
Another method I toyed around with was propagating values to nodes based on the safest path to that node while doing a DFS search, but not all values were guaranteed to update.
I still want to try to solve this myself, but I'm really stuck right now. Was wondering if there were any hints I could get. There are much simpler ways of doing this if it weren't for the O(|E|) time. Djikstras with creating some edge weights would work, but wouldn't be within the time bound.
graphs
$endgroup$
Was doing a little interview prep. Given an undirected graph G, such that each node is colored red or blue and |E|≥|V|, find a path in O(|E|) time such that starting and ending at 2 blue nodes, s and t, that you pass through as few red nodes as possible.
Initial Impressions: Since |E|≥|V|, O(|E|) time would include O(|E|+|V|), which means the solution likely uses BFS or DFS. Modifying the graph such that causing the all red nodes must be forced down a directed path of some long length (after making the whole graph directed) in order to use out-of-the-box BFS seems not viable, as it would mean constructing a new graph would be along O(|E||V|) time.
Another method I toyed around with was propagating values to nodes based on the safest path to that node while doing a DFS search, but not all values were guaranteed to update.
I still want to try to solve this myself, but I'm really stuck right now. Was wondering if there were any hints I could get. There are much simpler ways of doing this if it weren't for the O(|E|) time. Djikstras with creating some edge weights would work, but wouldn't be within the time bound.
graphs
graphs
asked Apr 1 at 17:42
user-2147481704user-2147481704
454
454
1
$begingroup$
Try a variant of BFS in which you first find all red nodes reachable only via blue nodes, and so on.
$endgroup$
– Yuval Filmus
Apr 1 at 20:22
add a comment |
1
$begingroup$
Try a variant of BFS in which you first find all red nodes reachable only via blue nodes, and so on.
$endgroup$
– Yuval Filmus
Apr 1 at 20:22
1
1
$begingroup$
Try a variant of BFS in which you first find all red nodes reachable only via blue nodes, and so on.
$endgroup$
– Yuval Filmus
Apr 1 at 20:22
$begingroup$
Try a variant of BFS in which you first find all red nodes reachable only via blue nodes, and so on.
$endgroup$
– Yuval Filmus
Apr 1 at 20:22
add a comment |
2 Answers
2
active
oldest
votes
$begingroup$
To solve this, you need to use $BFS$. But first, manipulate $G$ so that the path will always favor blue vertices.
The solution has 2 parts:
- Use $DFS$ on blue vertices only, to find all all-blue connected components. Let's denote each such component by $v'$. Now, each blue $v in v'$ will be "compressed" to a single vertex $u$, and an edge $(u,x)$ will be added for every $x in N(v')$.
Note any such $x$ is necessarily red.
This step costs $O(V+E) = O(E)$, since $DFS$ is $O(V+E)$, and you have at most $V$ blue vertices, which make no more than $E$ new edges to add.
Step 1 means all paths that are blue-only will be free. On the new graph, the $BFS$ will only consider the edges which pass through a red vertex.
- Use $BFS$ from $s$. That length of the path to $t$ will essentially be the shortest path under the constraint of least red vertices in the path.
$endgroup$
2
$begingroup$
the graph is undirected, so step 1 should be to find all all-blue connected components, not SCCs, right?
$endgroup$
– Kevin Wang
Apr 1 at 23:27
$begingroup$
@KevinWang yes, I will fix it
$endgroup$
– lox
Apr 2 at 8:18
add a comment |
$begingroup$
Convert $G$ to a directed graph $G'$ where we have two edges $(u,v)$ and $(v,u)$ in $G'$ for every edge $u,v$ in $G$. Let the length of $(u,v)$ be 1 if $v$ is a red node and 0 otherwise. Now run Dijkstra's algorithm on $G'$ from the starting node $s$ to the ending node $t$.
It is clear that the shortest path thus found passes as few red nodes as possible.
While we are running Dijkstra's algorithm, we are in one of two kinds of stages alternatively. One kind of stage is when we are exploring towards red nodes. The other kind of stage is when we are exploring towards blue nodes. Since each edge is checked/visited as most twice, the running time is $O(|E|)$.
$endgroup$
$begingroup$
Yeah that definitely works, but the runtime of Dijkstra's is O(|E| + |V|log|V|) which is more than O(|E|).
$endgroup$
– user-2147481704
Apr 1 at 22:26
$begingroup$
As explained, the running time is $O(|E|)$.
$endgroup$
– Apass.Jack
Apr 3 at 0:36
add a comment |
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2 Answers
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active
oldest
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2 Answers
2
active
oldest
votes
active
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votes
active
oldest
votes
$begingroup$
To solve this, you need to use $BFS$. But first, manipulate $G$ so that the path will always favor blue vertices.
The solution has 2 parts:
- Use $DFS$ on blue vertices only, to find all all-blue connected components. Let's denote each such component by $v'$. Now, each blue $v in v'$ will be "compressed" to a single vertex $u$, and an edge $(u,x)$ will be added for every $x in N(v')$.
Note any such $x$ is necessarily red.
This step costs $O(V+E) = O(E)$, since $DFS$ is $O(V+E)$, and you have at most $V$ blue vertices, which make no more than $E$ new edges to add.
Step 1 means all paths that are blue-only will be free. On the new graph, the $BFS$ will only consider the edges which pass through a red vertex.
- Use $BFS$ from $s$. That length of the path to $t$ will essentially be the shortest path under the constraint of least red vertices in the path.
$endgroup$
2
$begingroup$
the graph is undirected, so step 1 should be to find all all-blue connected components, not SCCs, right?
$endgroup$
– Kevin Wang
Apr 1 at 23:27
$begingroup$
@KevinWang yes, I will fix it
$endgroup$
– lox
Apr 2 at 8:18
add a comment |
$begingroup$
To solve this, you need to use $BFS$. But first, manipulate $G$ so that the path will always favor blue vertices.
The solution has 2 parts:
- Use $DFS$ on blue vertices only, to find all all-blue connected components. Let's denote each such component by $v'$. Now, each blue $v in v'$ will be "compressed" to a single vertex $u$, and an edge $(u,x)$ will be added for every $x in N(v')$.
Note any such $x$ is necessarily red.
This step costs $O(V+E) = O(E)$, since $DFS$ is $O(V+E)$, and you have at most $V$ blue vertices, which make no more than $E$ new edges to add.
Step 1 means all paths that are blue-only will be free. On the new graph, the $BFS$ will only consider the edges which pass through a red vertex.
- Use $BFS$ from $s$. That length of the path to $t$ will essentially be the shortest path under the constraint of least red vertices in the path.
$endgroup$
2
$begingroup$
the graph is undirected, so step 1 should be to find all all-blue connected components, not SCCs, right?
$endgroup$
– Kevin Wang
Apr 1 at 23:27
$begingroup$
@KevinWang yes, I will fix it
$endgroup$
– lox
Apr 2 at 8:18
add a comment |
$begingroup$
To solve this, you need to use $BFS$. But first, manipulate $G$ so that the path will always favor blue vertices.
The solution has 2 parts:
- Use $DFS$ on blue vertices only, to find all all-blue connected components. Let's denote each such component by $v'$. Now, each blue $v in v'$ will be "compressed" to a single vertex $u$, and an edge $(u,x)$ will be added for every $x in N(v')$.
Note any such $x$ is necessarily red.
This step costs $O(V+E) = O(E)$, since $DFS$ is $O(V+E)$, and you have at most $V$ blue vertices, which make no more than $E$ new edges to add.
Step 1 means all paths that are blue-only will be free. On the new graph, the $BFS$ will only consider the edges which pass through a red vertex.
- Use $BFS$ from $s$. That length of the path to $t$ will essentially be the shortest path under the constraint of least red vertices in the path.
$endgroup$
To solve this, you need to use $BFS$. But first, manipulate $G$ so that the path will always favor blue vertices.
The solution has 2 parts:
- Use $DFS$ on blue vertices only, to find all all-blue connected components. Let's denote each such component by $v'$. Now, each blue $v in v'$ will be "compressed" to a single vertex $u$, and an edge $(u,x)$ will be added for every $x in N(v')$.
Note any such $x$ is necessarily red.
This step costs $O(V+E) = O(E)$, since $DFS$ is $O(V+E)$, and you have at most $V$ blue vertices, which make no more than $E$ new edges to add.
Step 1 means all paths that are blue-only will be free. On the new graph, the $BFS$ will only consider the edges which pass through a red vertex.
- Use $BFS$ from $s$. That length of the path to $t$ will essentially be the shortest path under the constraint of least red vertices in the path.
edited Apr 2 at 8:19
answered Apr 1 at 20:53
loxlox
4456
4456
2
$begingroup$
the graph is undirected, so step 1 should be to find all all-blue connected components, not SCCs, right?
$endgroup$
– Kevin Wang
Apr 1 at 23:27
$begingroup$
@KevinWang yes, I will fix it
$endgroup$
– lox
Apr 2 at 8:18
add a comment |
2
$begingroup$
the graph is undirected, so step 1 should be to find all all-blue connected components, not SCCs, right?
$endgroup$
– Kevin Wang
Apr 1 at 23:27
$begingroup$
@KevinWang yes, I will fix it
$endgroup$
– lox
Apr 2 at 8:18
2
2
$begingroup$
the graph is undirected, so step 1 should be to find all all-blue connected components, not SCCs, right?
$endgroup$
– Kevin Wang
Apr 1 at 23:27
$begingroup$
the graph is undirected, so step 1 should be to find all all-blue connected components, not SCCs, right?
$endgroup$
– Kevin Wang
Apr 1 at 23:27
$begingroup$
@KevinWang yes, I will fix it
$endgroup$
– lox
Apr 2 at 8:18
$begingroup$
@KevinWang yes, I will fix it
$endgroup$
– lox
Apr 2 at 8:18
add a comment |
$begingroup$
Convert $G$ to a directed graph $G'$ where we have two edges $(u,v)$ and $(v,u)$ in $G'$ for every edge $u,v$ in $G$. Let the length of $(u,v)$ be 1 if $v$ is a red node and 0 otherwise. Now run Dijkstra's algorithm on $G'$ from the starting node $s$ to the ending node $t$.
It is clear that the shortest path thus found passes as few red nodes as possible.
While we are running Dijkstra's algorithm, we are in one of two kinds of stages alternatively. One kind of stage is when we are exploring towards red nodes. The other kind of stage is when we are exploring towards blue nodes. Since each edge is checked/visited as most twice, the running time is $O(|E|)$.
$endgroup$
$begingroup$
Yeah that definitely works, but the runtime of Dijkstra's is O(|E| + |V|log|V|) which is more than O(|E|).
$endgroup$
– user-2147481704
Apr 1 at 22:26
$begingroup$
As explained, the running time is $O(|E|)$.
$endgroup$
– Apass.Jack
Apr 3 at 0:36
add a comment |
$begingroup$
Convert $G$ to a directed graph $G'$ where we have two edges $(u,v)$ and $(v,u)$ in $G'$ for every edge $u,v$ in $G$. Let the length of $(u,v)$ be 1 if $v$ is a red node and 0 otherwise. Now run Dijkstra's algorithm on $G'$ from the starting node $s$ to the ending node $t$.
It is clear that the shortest path thus found passes as few red nodes as possible.
While we are running Dijkstra's algorithm, we are in one of two kinds of stages alternatively. One kind of stage is when we are exploring towards red nodes. The other kind of stage is when we are exploring towards blue nodes. Since each edge is checked/visited as most twice, the running time is $O(|E|)$.
$endgroup$
$begingroup$
Yeah that definitely works, but the runtime of Dijkstra's is O(|E| + |V|log|V|) which is more than O(|E|).
$endgroup$
– user-2147481704
Apr 1 at 22:26
$begingroup$
As explained, the running time is $O(|E|)$.
$endgroup$
– Apass.Jack
Apr 3 at 0:36
add a comment |
$begingroup$
Convert $G$ to a directed graph $G'$ where we have two edges $(u,v)$ and $(v,u)$ in $G'$ for every edge $u,v$ in $G$. Let the length of $(u,v)$ be 1 if $v$ is a red node and 0 otherwise. Now run Dijkstra's algorithm on $G'$ from the starting node $s$ to the ending node $t$.
It is clear that the shortest path thus found passes as few red nodes as possible.
While we are running Dijkstra's algorithm, we are in one of two kinds of stages alternatively. One kind of stage is when we are exploring towards red nodes. The other kind of stage is when we are exploring towards blue nodes. Since each edge is checked/visited as most twice, the running time is $O(|E|)$.
$endgroup$
Convert $G$ to a directed graph $G'$ where we have two edges $(u,v)$ and $(v,u)$ in $G'$ for every edge $u,v$ in $G$. Let the length of $(u,v)$ be 1 if $v$ is a red node and 0 otherwise. Now run Dijkstra's algorithm on $G'$ from the starting node $s$ to the ending node $t$.
It is clear that the shortest path thus found passes as few red nodes as possible.
While we are running Dijkstra's algorithm, we are in one of two kinds of stages alternatively. One kind of stage is when we are exploring towards red nodes. The other kind of stage is when we are exploring towards blue nodes. Since each edge is checked/visited as most twice, the running time is $O(|E|)$.
edited Apr 1 at 23:32
answered Apr 1 at 22:13
Apass.JackApass.Jack
14.3k1940
14.3k1940
$begingroup$
Yeah that definitely works, but the runtime of Dijkstra's is O(|E| + |V|log|V|) which is more than O(|E|).
$endgroup$
– user-2147481704
Apr 1 at 22:26
$begingroup$
As explained, the running time is $O(|E|)$.
$endgroup$
– Apass.Jack
Apr 3 at 0:36
add a comment |
$begingroup$
Yeah that definitely works, but the runtime of Dijkstra's is O(|E| + |V|log|V|) which is more than O(|E|).
$endgroup$
– user-2147481704
Apr 1 at 22:26
$begingroup$
As explained, the running time is $O(|E|)$.
$endgroup$
– Apass.Jack
Apr 3 at 0:36
$begingroup$
Yeah that definitely works, but the runtime of Dijkstra's is O(|E| + |V|log|V|) which is more than O(|E|).
$endgroup$
– user-2147481704
Apr 1 at 22:26
$begingroup$
Yeah that definitely works, but the runtime of Dijkstra's is O(|E| + |V|log|V|) which is more than O(|E|).
$endgroup$
– user-2147481704
Apr 1 at 22:26
$begingroup$
As explained, the running time is $O(|E|)$.
$endgroup$
– Apass.Jack
Apr 3 at 0:36
$begingroup$
As explained, the running time is $O(|E|)$.
$endgroup$
– Apass.Jack
Apr 3 at 0:36
add a comment |
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$begingroup$
Try a variant of BFS in which you first find all red nodes reachable only via blue nodes, and so on.
$endgroup$
– Yuval Filmus
Apr 1 at 20:22