Find a path from s to t using as few red nodes as possible The Next CEO of Stack OverflowDijkstra 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



The Next CEO of Stack OverflowDijkstra 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










3












$begingroup$


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.










share|cite|improve this question









$endgroup$







  • 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
    3 hours ago















3












$begingroup$


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.










share|cite|improve this question









$endgroup$







  • 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
    3 hours ago













3












3








3





$begingroup$


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.










share|cite|improve this question









$endgroup$




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






share|cite|improve this question













share|cite|improve this question











share|cite|improve this question




share|cite|improve this question










asked 6 hours ago









Hunter DyerHunter Dyer

334




334







  • 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
    3 hours ago












  • 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
    3 hours ago







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
3 hours ago




$begingroup$
Try a variant of BFS in which you first find all red nodes reachable only via blue nodes, and so on.
$endgroup$
– Yuval Filmus
3 hours ago










2 Answers
2






active

oldest

votes


















4












$begingroup$

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:



  1. Use $DFS$ on blue vertices only, to find all all-blue strongly connected components, or $SCC$. Let's denote each $SCC$ 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.



  1. 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.





share|cite|improve this answer











$endgroup$












  • $begingroup$
    the graph is undirected, so step 1 should be to find all all-blue connected components, not SCCs, right?
    $endgroup$
    – Kevin Wang
    17 mins ago










  • $begingroup$
    I believe that is a typo by lox. Yes, it should be connected components instead of SCC.
    $endgroup$
    – Apass.Jack
    9 mins ago


















1












$begingroup$

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 $O(|E|)$.






share|cite|improve this answer











$endgroup$












  • $begingroup$
    Yeah that definitely works, but the runtime of Dijkstra's is O(|E| + |V|log|V|) which is more than O(|E|).
    $endgroup$
    – Hunter Dyer
    1 hour ago










  • $begingroup$
    I will show shortly that this particular run of Dijkstra's algorithm actually takes $O(|E|)$ time.
    $endgroup$
    – Apass.Jack
    1 hour ago












Your Answer





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2 Answers
2






active

oldest

votes








2 Answers
2






active

oldest

votes









active

oldest

votes






active

oldest

votes









4












$begingroup$

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:



  1. Use $DFS$ on blue vertices only, to find all all-blue strongly connected components, or $SCC$. Let's denote each $SCC$ 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.



  1. 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.





share|cite|improve this answer











$endgroup$












  • $begingroup$
    the graph is undirected, so step 1 should be to find all all-blue connected components, not SCCs, right?
    $endgroup$
    – Kevin Wang
    17 mins ago










  • $begingroup$
    I believe that is a typo by lox. Yes, it should be connected components instead of SCC.
    $endgroup$
    – Apass.Jack
    9 mins ago















4












$begingroup$

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:



  1. Use $DFS$ on blue vertices only, to find all all-blue strongly connected components, or $SCC$. Let's denote each $SCC$ 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.



  1. 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.





share|cite|improve this answer











$endgroup$












  • $begingroup$
    the graph is undirected, so step 1 should be to find all all-blue connected components, not SCCs, right?
    $endgroup$
    – Kevin Wang
    17 mins ago










  • $begingroup$
    I believe that is a typo by lox. Yes, it should be connected components instead of SCC.
    $endgroup$
    – Apass.Jack
    9 mins ago













4












4








4





$begingroup$

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:



  1. Use $DFS$ on blue vertices only, to find all all-blue strongly connected components, or $SCC$. Let's denote each $SCC$ 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.



  1. 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.





share|cite|improve this answer











$endgroup$



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:



  1. Use $DFS$ on blue vertices only, to find all all-blue strongly connected components, or $SCC$. Let's denote each $SCC$ 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.



  1. 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.






share|cite|improve this answer














share|cite|improve this answer



share|cite|improve this answer








edited 26 mins ago









templatetypedef

5,59911945




5,59911945










answered 2 hours ago









loxlox

1866




1866











  • $begingroup$
    the graph is undirected, so step 1 should be to find all all-blue connected components, not SCCs, right?
    $endgroup$
    – Kevin Wang
    17 mins ago










  • $begingroup$
    I believe that is a typo by lox. Yes, it should be connected components instead of SCC.
    $endgroup$
    – Apass.Jack
    9 mins ago
















  • $begingroup$
    the graph is undirected, so step 1 should be to find all all-blue connected components, not SCCs, right?
    $endgroup$
    – Kevin Wang
    17 mins ago










  • $begingroup$
    I believe that is a typo by lox. Yes, it should be connected components instead of SCC.
    $endgroup$
    – Apass.Jack
    9 mins ago















$begingroup$
the graph is undirected, so step 1 should be to find all all-blue connected components, not SCCs, right?
$endgroup$
– Kevin Wang
17 mins ago




$begingroup$
the graph is undirected, so step 1 should be to find all all-blue connected components, not SCCs, right?
$endgroup$
– Kevin Wang
17 mins ago












$begingroup$
I believe that is a typo by lox. Yes, it should be connected components instead of SCC.
$endgroup$
– Apass.Jack
9 mins ago




$begingroup$
I believe that is a typo by lox. Yes, it should be connected components instead of SCC.
$endgroup$
– Apass.Jack
9 mins ago











1












$begingroup$

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 $O(|E|)$.






share|cite|improve this answer











$endgroup$












  • $begingroup$
    Yeah that definitely works, but the runtime of Dijkstra's is O(|E| + |V|log|V|) which is more than O(|E|).
    $endgroup$
    – Hunter Dyer
    1 hour ago










  • $begingroup$
    I will show shortly that this particular run of Dijkstra's algorithm actually takes $O(|E|)$ time.
    $endgroup$
    – Apass.Jack
    1 hour ago
















1












$begingroup$

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 $O(|E|)$.






share|cite|improve this answer











$endgroup$












  • $begingroup$
    Yeah that definitely works, but the runtime of Dijkstra's is O(|E| + |V|log|V|) which is more than O(|E|).
    $endgroup$
    – Hunter Dyer
    1 hour ago










  • $begingroup$
    I will show shortly that this particular run of Dijkstra's algorithm actually takes $O(|E|)$ time.
    $endgroup$
    – Apass.Jack
    1 hour ago














1












1








1





$begingroup$

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 $O(|E|)$.






share|cite|improve this answer











$endgroup$



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 $O(|E|)$.







share|cite|improve this answer














share|cite|improve this answer



share|cite|improve this answer








edited 12 mins ago

























answered 1 hour ago









Apass.JackApass.Jack

13.7k1940




13.7k1940











  • $begingroup$
    Yeah that definitely works, but the runtime of Dijkstra's is O(|E| + |V|log|V|) which is more than O(|E|).
    $endgroup$
    – Hunter Dyer
    1 hour ago










  • $begingroup$
    I will show shortly that this particular run of Dijkstra's algorithm actually takes $O(|E|)$ time.
    $endgroup$
    – Apass.Jack
    1 hour ago

















  • $begingroup$
    Yeah that definitely works, but the runtime of Dijkstra's is O(|E| + |V|log|V|) which is more than O(|E|).
    $endgroup$
    – Hunter Dyer
    1 hour ago










  • $begingroup$
    I will show shortly that this particular run of Dijkstra's algorithm actually takes $O(|E|)$ time.
    $endgroup$
    – Apass.Jack
    1 hour ago
















$begingroup$
Yeah that definitely works, but the runtime of Dijkstra's is O(|E| + |V|log|V|) which is more than O(|E|).
$endgroup$
– Hunter Dyer
1 hour ago




$begingroup$
Yeah that definitely works, but the runtime of Dijkstra's is O(|E| + |V|log|V|) which is more than O(|E|).
$endgroup$
– Hunter Dyer
1 hour ago












$begingroup$
I will show shortly that this particular run of Dijkstra's algorithm actually takes $O(|E|)$ time.
$endgroup$
– Apass.Jack
1 hour ago





$begingroup$
I will show shortly that this particular run of Dijkstra's algorithm actually takes $O(|E|)$ time.
$endgroup$
– Apass.Jack
1 hour ago


















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Where is the suspend/hibernate button in GNOME Shell? Announcing the arrival of Valued Associate #679: Cesar Manara Planned maintenance scheduled April 23, 2019 at 23:30 UTC (7:30pm US/Eastern)No suspend option in UI on Bionic BeaverHow can I set sleep mode in ubuntu18.04 LTS and what is the short cut key to do so?17.10 suspend not availableUbuntu 18.04 LTS missing sleep optionUbuntu 18.04 LTS - missing suspend option when power button is pressedHow to put Thinkpad X1 Extreme to sleep in Ubuntu 18.10?Suspend Button in interactive power button menu18.04 - Keep programs running after logging outway to disable Hibernate from within gconf-editor so button disappears?How can I hibernate from GNOME Shell?How can I hibernate/suspend from the command line and do so at a specific timeNo permission to suspend/hibernate after upgrading to 12.10MATE - Missing Suspend and Hibernate buttons, pressing power button shutdowns system immediatelyUbuntu 14.04: Suspend, Hibernate and Suspend-hybrid in the menu?Change “power-button-action” comand for “hibernate” option in GNOME 3.18Shutdown / Power off button does always go to suspend on 17.10Hibernate after suspend stopped working in 17.10Why doesn't the keyboard screenshot button work on Ubuntu with GNOME shell?