Lecture14-Single-SourceShortestPaths

Lecture14-Single-SourceShortestPaths - Single-Source...

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Unformatted text preview: Single-Source Shortest Paths Shortest-path problem •ºI –+ • G=(V,E) G Weighted Directed Graph( G G )G Weight function w: ERª ˆ ¶ ’… E G v0 G vk G Path( G • G p=(v0,v1,…,vk) G G ) Single-Source Shortest Paths 2 Shortest-path problem •i •i w( p ) = ∑i =1 w(vi −1 , vi ) k u G v. B ·ª p min{w( p ) : u → v}, ∃a path from u to v. δ (u , v) = ∞, otherwise. Single-Source Shortest Paths 3 Shortest-path tree rooted at s •i G=(V,E) G Shortest-path tree rooted at s ( G ’ª s) ¸ · x ) G’=(V’,E’))¸ ’ª ·x G – V’ G ª s) ¸ ’ ·x – G’ G sG Rooted Tree G – G G’ G s G v G simple path G GG sG vG ª · )¸ x Single-Source Shortest Paths 4 Shortest-path tree rooted at s i s 1 t 1 v 10 1 1 10 y 1 10 10 x 10 u 10 v 1 y w 1 t 1 1 10 s 10 x w z z Original Graph G Shortest-path tree rooted at s 5 Single-Source Shortest Paths Predecessor graph •i G=(V,E) h ’ª · W Ç Gπ=(Vπ,EW π)Ç h ’ª · – π[s]=NIL G s∈Vπ G ’ª · W π h Ç – G π[v]≠NIL G (π[v],v)∈Eπ G v∈Vπ G • Shortest-path tree rooted at s G Predecessor graph G G Single-Source Shortest Paths 6 Predecessor graph i π[s] NIL 1 t 1 v 10 1 1 10 y 1 π[t] s s π[u] NIL 10 10 x 10 π[v] t π[w] s 1 π[x] t s π[y] x 10 π[z] v w 1 u 10 v t 1 10 y 1 x w z Single-Source Shortest Paths z 7 Original Graph G Shortest-path tree rooted at s Initialize-Single-Source i •i G •G G •G GªI– · º sc˜p l– . ¡ *p d[v]x ª E¨* · sG vG π[v]x ª E¨* · vx ª E¨* · s G vx ª E¨ · d[v]=∞ G π[v]=NIL G d[s]=0 G s Single-Source Shortest Paths 8 Initialize-Single-Source i Initialize-Single-Source(G,s) { for each vertex v∈V[G] do d[v]∞ π[v]NIL d[s]0 } Single-Source Shortest Paths 9 Relaxation i • ýP ª · ^ -Ø* (u,v) P Relax(u,v,w) { if d[v]>d[u]+w(u,v) then d[v]d[u]+w(u,v) π[v]u } Single-Source Shortest Paths 10 Relaxation i Relax(u,v,w) G s 4 u 4 u w(u,v) 7 v s if w(u,v)=4 (>3) ª xÈ ·, G sv G w(u,v) 6 v Relax(u,v,w) G s if w(u,v)=2 (<3) G G sª v È ·, x π[v]u 4 u Single-Source Shortest Paths w(u,v) 7 v 11 ª·WÌh · W •Ì hª* · W Ì hª ª · •W Ì h Relaxation i (u,v) G δ(s,v)≤δ(s,u)+w(u,v) G δ(s,v)≤d[v] G d[v] G ’ W v h sª · Ì G d[v]=δ(s,v) G Relaxation G G d[v] G Single-Source Shortest Paths 12 ª·W̨ · W •Ì ¨ª* i ª · •Ì ¨ W G sW v ¨ ’ª · Ì ª· WÌ ¨ s G v ¨Ìª* ·W Relaxation i d[v]=δ(s,v)=∞ G (u,v) G d[u]=δ(s,u) G Relax(u,v,w) G d[v]=δ(s,v) G Single-Source Shortest Paths 13 ª·W8 Ê Relaxation i • Path-relaxation G G p=(v0,v1,…,vk) G s=v0· vW k n ’ª Ê ª·Wn Ê Relax(v0,v1,w) G Relax(v1,v2,w)… G Relax(vk-1,vk,w) G d[vk]=δ(s,vk) G • Predecessor graph G ’ ª · W Ên Relaxation Ê n ’ª · W vG d[v]=δ(s,v)W n ’ª · Ê Predecessor graph Gπ G Shortest-path tree rooted at s G Single-Source Shortest Paths 14 Bellman-Ford i – g¡ · *p W ˜IÆ º • +ª Bellman-Ford(G,w,s) { Initialize-Single-Source(G,s) for i = 1 to |V-1| do for each edge (u,v)∈E do Relex(u,v,w) for each edge (u,v)∈E do if d[v]>d[u]+w(u,v) then return false fª · // ˆ WÉ return true fª · // ˆ WÉ } Single-Source Shortest Paths 15 Bellman-Ford ø * ª·W Ë 5 (a) 6 s0 7 8 ∞ -2 -3 -4 ∞ 2 9 ∞ ∞ 7 (b) 6 s0 7 8 6 5 -2 -3 -4 7 2 9 ∞ ∞ 7 Single-Source Shortest Paths 16 Bellman-Ford x * ªµì j 5 (c) 6 s0 7 8 6 -2 -3 -4 7 2 9 2 4 7 (d) (e) 6 s0 7 8 2 5 -2 -3 -4 7 2 9 -2 4 7 Single-Source Shortest Paths 17 Bellman-Ford ¸ ª·W Ê •· Í J ¨ Relaxation G Shortest-path tree rootedª atW s ¸ ’· Ê path G ’ª · W Ê ¸ path-relaxation ¸ ª ·W Ê |V|-1 G ’ ª · W ¸Ê Shortest simple path G v G d[v]=δ(s,v) G Single-Source Shortest Paths 18 Bellman-Ford h ª ·u . •· Ì = ø – Initialize-Single-Source G ’– x·h W ª O(|V|) G O(|V||E|) G –G O(|E|) · Ì ]À •W ª x·h O(|V||E|) G Single-Source Shortest Paths 19 O(|V|) G Relaxation G Single-source shortest paths in DAGs • i Bellman-Fordº –I– Relaxationº –– I DAG-Shortest-Path(G,w,s) { Topologically sort V[G] Initialize-Single-Source(G,s) for each u taken in topological order do for each v∈adj[u] do Relax(u,v,w) } µ ì •j xªf O(|V|+|E|) G Single-Source Shortest Paths 20 DAG-Shortest-Path G (a ) 5s 2 7 -1 -2 ∞ 0 ∞ ∞ ∞ ∞ 3 4 2 6 1 (b ) 5s 2 7 -1 -2 ∞ 0 ∞ ∞ ∞ ∞ 3 4 2 6 1 Single-Source Shortest Paths 21 DAG-Shortest-Path G (c ) 5s 2 ∞ 0 3 6 2 7 6 4 -1 2 1 ∞ -2 ∞ (d ) 5s 2 ∞ 0 3 6 2 7 6 4 -1 2 1 6 -2 4 Single-Source Shortest Paths 22 DAG-Shortest-Path G (e ) 5s 2 ∞ 0 3 6 2 7 6 4 -1 2 (f) 5s 2 ∞ 0 3 6 2 7 6 4 -1 2 (g ) 6 2 7 6 4 -1 2 Single-Source Shortest Paths 23 1 5 -2 4 1 5 -2 3 5s 2 ∞ 0 3 1 5 -2 3 Dijkstra i •I ˜ • i Bellman-fordº –I– G Relaxation· δ ’ ª \S •G •–º – I Single-Source Shortest Paths 24 Priority queue G Dijkstra i Q: Priority queue with d as the key Dijkstra(G,w,s) { Initialize-Single-Source(G,s) Q=V[G] while Q is not empty do u=Extract-Min(Q) for each v∈adj[u] do Relax(u,v,w) } Single-Source Shortest Paths 25 Dijkstra ˜ * ª µñP (a) 10 s 2 0 5 ∞ 3 1 ∞ 9 4 7 ∞ 2 ∞ 6 s (b) 10 2 0 5 10 3 1 ∞ 9 4 7 5 2 ∞ 6 Single-Source Shortest Paths 26 Dijkstra ø * ª ·\C (c) 10 s 0 5 2 8 3 1 14 9 4 7 5 2 7 6 s (d) 10 0 5 2 8 3 1 11 9 4 7 5 2 7 6 Single-Source Shortest Paths 27 Dijkstra x * ª ·\@ (e) 10 s 2 0 5 8 3 1 9 9 4 7 5 2 7 6 s (e) 10 2 0 5 8 3 1 9 9 4 7 5 2 7 6 Single-Source Shortest Paths 28 Dijkstra ¸ ª ·WÎ · W •Î ¸ª ’ª · W Î ¸ •G •G G •G G G Priority queue ¦x Linear array ¸ ’ª · W Î Binary ’ª · W Î ¸ heap O(|V|2) G O(|E|log|V|) G Fibonacci ’heap ¸ ª · WÎ Single-Source Shortest Paths O(|E|+|V|log|V|) 29 ...
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This note was uploaded on 06/05/2010 for the course COMPUTER S 700 taught by Professor Joewhite during the Spring '10 term at Universidad San Martín de Porres.

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