# Algoritma Traversal Graph. Graph Traversal Algorithms In general, graphs do not have a vertex, like a root, that initiates unique paths to each of the.

## Presentation on theme: "Algoritma Traversal Graph. Graph Traversal Algorithms In general, graphs do not have a vertex, like a root, that initiates unique paths to each of the."— Presentation transcript:

Algoritma Traversal Graph

Graph Traversal Algorithms In general, graphs do not have a vertex, like a root, that initiates unique paths to each of the vertices. From any starting vertex in a graph, it might not be possible to search all of the vertices. In addition, a graph could have a cycle that results in multiple visits to a vertex. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Graph Traversal Algorithms (continued) The breadth-first search visits vertices in the order of their path length from a starting vertex. It may not visit every vertex of the graph The depth-first search traverses all the vertices of a graph by making a series of recursive calls that follow paths through the graph. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Graph Traversal Algorithms (continued) Graph algorithms discern the state of a vertex during the algorithm by using the colors WHITE, GRAY, and BLACK. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Breadth-First Search Algorithm (continued) Color all vertices of the sample graph WHITE and push the starting vertex (A) onto the queue visitQueue. Pop A from the queue, color it BLACK, and insert it into visitList, which is the list of visited vertices. Push all WHITE neighbors onto the queue. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Breadth-First Search Algorithm (continued) Pop B from the queue and place it in visitList with color BLACK. The only adjacent vertex for B is D, which is still colored WHITE. Color D GRAY and add it to the queue © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Breadth-First Search Algorithm (continued) Pop vertex G from the queue and place it in visitList. G has no adjacent vertices, so pop D from the queue. The neighbors, E and F, enter the queue. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

bfs() // perform the breadth-first traversal // from sVertex and return the list // of visited vertices public static LinkedList bfs( DiGraph g, T sVertex) { // queue stores adjacent vertices; list // stores visited vertices LinkedQueue visitQueue = new LinkedQueue (); LinkedList visitList = new LinkedList (); // set and iterator retrieve and scan // neighbors of a vertex Set edgeSet; Iterator edgeIter; T currVertex = null, neighborVertex = null;

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. bfs() (continued) // check that starting vertex is valid if (!g.containsVertex(sVertex)) throw new IllegalArgumentException( "bfs(): starting vertex not in the graph"); // color all vertices WHITE g.colorWhite(); // initialize queue with starting vertex visitQueue.push(sVertex); while (!visitQueue.isEmpty()) { // remove a vertex from the queue, color // it black, and add to the list of // visited vertices currVertex = visitQueue.pop(); g.setColor(currVertex,VertexColor.BLACK); visitList.add(currVertex);

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. bfs() (continued) // obtain the set of neighbors for current vertex edgeSet = g.getNeighbors(currVertex); // sequence through the neighbors and look // for vertices that have not been visited edgeIter = edgeSet.iterator(); while (edgeIter.hasNext()) { neighborVertex = edgeIter.next();

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. bfs() (concluded) if (g.getColor(neighborVertex) == VertexColor.WHITE) { // color unvisited vertex GRAY and // push it onto queue g.setColor(neighborVertex,VertexColor.GRAY); visitQueue.push(neighborVertex); } return visitList; }

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. bfs() (concluded) if (g.getColor(neighborVertex) == VertexColor.WHITE) { // color unvisited vertex GRAY and // push it onto queue g.setColor(neighborVertex,VertexColor.GRAY); visitQueue.push(neighborVertex); } return visitList; }

Running Time of Breadth-First Search The running time for the breadth-first search is O(V + E), where V is the number of vertices and E is the number of edges. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Breadth-First Search Example © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. // create a graph g and declare startVertex and visitList DiGraph g = DiGraph.readGraph("bfsgraph.dat"); String startVertex; List visitList;... // call bfs() with arguments g and startVertx visitList = DiGraphs.bfs(g, startVertex); // output the visitList System.out.println("BFS visitList from " + startVertex + ": " + visitList);

Breadth-First Search Example (concluded) © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. Output: Run 1: (startVertex = "A") BFS visitList from A: [A, G, B, C, D, E, F] Run 2: (startVertex = "D") BFS visitList from D: [D, E, F, G] Run 3: (startVertex = "E") BFS visitList from E: [E]

Depth-First Visit The depth-first visit algorithm is modeled after the recursive postorder scan of a binary tree. In the tree, a node is visited only after visits are made to all of the nodes in its subtree. In the graph, a node is visited only after visiting all of the nodes in paths that emanate from the node. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Depth-First Visit (continued) Backtrack to the previous recursive step and look for another adjacent vertex and launch a scan down its paths. There is no ordering among vertices in an adjacency list, so the paths and hence the order of visits to vertices can vary. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Depth-First Visit (continued) Discover A (color GRAY) Discover B (color GRAY) Discover D (color GRAY) Discover E (color GRAY, then BLACK) Backtrack D (color BLACK) Backtrack B (color BLACK) Backtrack A (A remains GRAY) Discover C (color BLACK) Backtrack A (color BLACK). Visit complete. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Depth-First Visit (continued) The depth ‑ first visit is a recursive algorithm that distinguishes the discovery and finishing time (when a vertex becomes BLACK) of a vertex. The depth ‑ first visit returns a list of the vertices found in the reverse order of their finishing times. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Depth-First Visit (continued) An edge that connects a vertex to a neighbor that has color GRAY is called a back edge. – A depth-first visit has a cycle if and only if it has a back edge. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

dfsVisit() // depth-first visit assuming a WHITE starting // vertex; dfsList contains the visited vertices in // reverse order of finishing time; when checkForCycle // is true, throws IllegalPathStateException if it // detects a cycle public static void dfsVisit(DiGraph g, T sVertex, LinkedList dfsList, boolean checkForCycle) { T neighborVertex; Set edgeSet; // iterator to scan the adjacency set of a vertex Iterator edgeIter; VertexColor color; if (!g.containsVertex(sVertex)) throw new IllegalArgumentException( "dfsVisit(): vertex not in the graph");

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. dfsVisit() (continued) // color vertex GRAY to note its discovery g.setColor(sVertex, VertexColor.GRAY); edgeSet = g.getNeighbors(sVertex); // sequence through the adjacency set and look // for vertices that are not yet discovered // (colored WHITE); recursively call dfsVisit() // for each such vertex; if a vertex in the adjacency // list is GRAY, the vertex was discovered during a // previous call and there is a cycle that begins and // ends at the vertex; if checkForCycle is true, // throw an exception edgeIter = edgeSet.iterator();

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. dfsVisit() (concluded) while (edgeIter.hasNext()) { neighborVertex = edgeIter.next(); color = g.getColor(neighborVertex); if (color == VertexColor.WHITE) dfsVisit(g, neighborVertex, dfsList, checkForCycle); else if (color == VertexColor.GRAY && checkForCycle) throw new IllegalPathStateException( "dfsVisit(): graph has a cycle"); } // finished with vertex sVertex; make it BLACK // and add it to the front of dfsList g.setColor(sVertex, VertexColor.BLACK); dfsList.addFirst(sVertex); }

Depth-First Visit Example (concluded) © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. finishOrder = new LinkedList (); g.colorWhite(); try { DiGraphs.dfsVisit(g, "E", finishOrder, true); System.out.println("finishOrder: " + finishOrder); } catch (IllegalPathStateException ipse) { System.out.println(ipse.getMessage()); } Output: dfsVisit(): cycle involving vertices D and E

Depth-First Search Algorithm Depth ‑ first search begins with all WHITE vertices and performs depth ‑ first visits until all vertices of the graph are BLACK. The algorithm returns a list of all vertices in the graph in the reverse order of their finishing times. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

dfs() // depth-first search; dfsList contains all // the graph vertices in the reverse order // of their finishing times public static void dfs(DiGraph g, LinkedList dfsList) { Iterator graphIter; T vertex = null; // clear dfsList dfsList.clear(); // initialize all vertices to WHITE g.colorWhite();

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. dfs() (concluded) // call dfsVisit() for each WHITE vertex graphIter = g.vertexSet().iterator(); while (graphIter.hasNext()) { vertex = graphIter.next(); if (g.getColor(vertex) == VertexColor.WHITE) dfsVisit(g, vertex, dfsList, false); }

Running Time for Depth-First Search An argument similar to that for the breadth- first search shows that that the running time for dfs() is O(V+E), where V is the number of vertices in the graph and E is the number of edges. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Depth-First Search Example © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. dfsVisit() starting at E followed by dfsVisit() starting at A dfsList: [A, B, C, E, F, G, D]

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. Program 24.2 import java.io.FileNotFoundException; import ds.util.DiGraph; import ds.util.DiGraphs; public class Program24_2 { public static void main(String[] args) throws FileNotFoundException { DiGraph g = DiGraph.readGraph("cycle.dat"); // determine if the graph is acyclic if (DiGraphs.acyclic(g)) System.out.println("Graph is acyclic"); else System.out.println("Graph is not acyclic");

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. Program 24.2 (concluded) // add edge (E,B) to create a cycle System.out.print(" Adding edge (E,B): "); g.addEdge("E", "B", 1); // retest the graph to see if it is acyclic if (DiGraphs.acyclic(g)) System.out.println("New graph is acyclic"); else System.out.println("New graph is not acyclic"); } Run: Graph is acyclic Adding edge (E,B): New graph is not acyclic

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# Algoritma Traversal Graph. Graph Traversal Algorithms In general, graphs do not have a vertex, like a root, that initiates unique paths to each of the.

## Presentation on theme: "Algoritma Traversal Graph. Graph Traversal Algorithms In general, graphs do not have a vertex, like a root, that initiates unique paths to each of the."— Presentation transcript:

Algoritma Traversal Graph

Graph Traversal Algorithms In general, graphs do not have a vertex, like a root, that initiates unique paths to each of the vertices. From any starting vertex in a graph, it might not be possible to search all of the vertices. In addition, a graph could have a cycle that results in multiple visits to a vertex. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Graph Traversal Algorithms (continued) The breadth-first search visits vertices in the order of their path length from a starting vertex. It may not visit every vertex of the graph The depth-first search traverses all the vertices of a graph by making a series of recursive calls that follow paths through the graph. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Graph Traversal Algorithms (continued) Graph algorithms discern the state of a vertex during the algorithm by using the colors WHITE, GRAY, and BLACK. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Breadth-First Search Algorithm (continued) Color all vertices of the sample graph WHITE and push the starting vertex (A) onto the queue visitQueue. Pop A from the queue, color it BLACK, and insert it into visitList, which is the list of visited vertices. Push all WHITE neighbors onto the queue. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Breadth-First Search Algorithm (continued) Pop B from the queue and place it in visitList with color BLACK. The only adjacent vertex for B is D, which is still colored WHITE. Color D GRAY and add it to the queue © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Breadth-First Search Algorithm (continued) Pop vertex G from the queue and place it in visitList. G has no adjacent vertices, so pop D from the queue. The neighbors, E and F, enter the queue. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

bfs() // perform the breadth-first traversal // from sVertex and return the list // of visited vertices public static LinkedList bfs( DiGraph g, T sVertex) { // queue stores adjacent vertices; list // stores visited vertices LinkedQueue visitQueue = new LinkedQueue (); LinkedList visitList = new LinkedList (); // set and iterator retrieve and scan // neighbors of a vertex Set edgeSet; Iterator edgeIter; T currVertex = null, neighborVertex = null;

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. bfs() (continued) // check that starting vertex is valid if (!g.containsVertex(sVertex)) throw new IllegalArgumentException( "bfs(): starting vertex not in the graph"); // color all vertices WHITE g.colorWhite(); // initialize queue with starting vertex visitQueue.push(sVertex); while (!visitQueue.isEmpty()) { // remove a vertex from the queue, color // it black, and add to the list of // visited vertices currVertex = visitQueue.pop(); g.setColor(currVertex,VertexColor.BLACK); visitList.add(currVertex);

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. bfs() (continued) // obtain the set of neighbors for current vertex edgeSet = g.getNeighbors(currVertex); // sequence through the neighbors and look // for vertices that have not been visited edgeIter = edgeSet.iterator(); while (edgeIter.hasNext()) { neighborVertex = edgeIter.next();

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. bfs() (concluded) if (g.getColor(neighborVertex) == VertexColor.WHITE) { // color unvisited vertex GRAY and // push it onto queue g.setColor(neighborVertex,VertexColor.GRAY); visitQueue.push(neighborVertex); } return visitList; }

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. bfs() (concluded) if (g.getColor(neighborVertex) == VertexColor.WHITE) { // color unvisited vertex GRAY and // push it onto queue g.setColor(neighborVertex,VertexColor.GRAY); visitQueue.push(neighborVertex); } return visitList; }

Running Time of Breadth-First Search The running time for the breadth-first search is O(V + E), where V is the number of vertices and E is the number of edges. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Breadth-First Search Example © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. // create a graph g and declare startVertex and visitList DiGraph g = DiGraph.readGraph("bfsgraph.dat"); String startVertex; List visitList;... // call bfs() with arguments g and startVertx visitList = DiGraphs.bfs(g, startVertex); // output the visitList System.out.println("BFS visitList from " + startVertex + ": " + visitList);

Breadth-First Search Example (concluded) © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. Output: Run 1: (startVertex = "A") BFS visitList from A: [A, G, B, C, D, E, F] Run 2: (startVertex = "D") BFS visitList from D: [D, E, F, G] Run 3: (startVertex = "E") BFS visitList from E: [E]

Depth-First Visit The depth-first visit algorithm is modeled after the recursive postorder scan of a binary tree. In the tree, a node is visited only after visits are made to all of the nodes in its subtree. In the graph, a node is visited only after visiting all of the nodes in paths that emanate from the node. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Depth-First Visit (continued) Backtrack to the previous recursive step and look for another adjacent vertex and launch a scan down its paths. There is no ordering among vertices in an adjacency list, so the paths and hence the order of visits to vertices can vary. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Depth-First Visit (continued) Discover A (color GRAY) Discover B (color GRAY) Discover D (color GRAY) Discover E (color GRAY, then BLACK) Backtrack D (color BLACK) Backtrack B (color BLACK) Backtrack A (A remains GRAY) Discover C (color BLACK) Backtrack A (color BLACK). Visit complete. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Depth-First Visit (continued) The depth ‑ first visit is a recursive algorithm that distinguishes the discovery and finishing time (when a vertex becomes BLACK) of a vertex. The depth ‑ first visit returns a list of the vertices found in the reverse order of their finishing times. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Depth-First Visit (continued) An edge that connects a vertex to a neighbor that has color GRAY is called a back edge. – A depth-first visit has a cycle if and only if it has a back edge. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

dfsVisit() // depth-first visit assuming a WHITE starting // vertex; dfsList contains the visited vertices in // reverse order of finishing time; when checkForCycle // is true, throws IllegalPathStateException if it // detects a cycle public static void dfsVisit(DiGraph g, T sVertex, LinkedList dfsList, boolean checkForCycle) { T neighborVertex; Set edgeSet; // iterator to scan the adjacency set of a vertex Iterator edgeIter; VertexColor color; if (!g.containsVertex(sVertex)) throw new IllegalArgumentException( "dfsVisit(): vertex not in the graph");

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. dfsVisit() (continued) // color vertex GRAY to note its discovery g.setColor(sVertex, VertexColor.GRAY); edgeSet = g.getNeighbors(sVertex); // sequence through the adjacency set and look // for vertices that are not yet discovered // (colored WHITE); recursively call dfsVisit() // for each such vertex; if a vertex in the adjacency // list is GRAY, the vertex was discovered during a // previous call and there is a cycle that begins and // ends at the vertex; if checkForCycle is true, // throw an exception edgeIter = edgeSet.iterator();

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. dfsVisit() (concluded) while (edgeIter.hasNext()) { neighborVertex = edgeIter.next(); color = g.getColor(neighborVertex); if (color == VertexColor.WHITE) dfsVisit(g, neighborVertex, dfsList, checkForCycle); else if (color == VertexColor.GRAY && checkForCycle) throw new IllegalPathStateException( "dfsVisit(): graph has a cycle"); } // finished with vertex sVertex; make it BLACK // and add it to the front of dfsList g.setColor(sVertex, VertexColor.BLACK); dfsList.addFirst(sVertex); }

Depth-First Visit Example (concluded) © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. finishOrder = new LinkedList (); g.colorWhite(); try { DiGraphs.dfsVisit(g, "E", finishOrder, true); System.out.println("finishOrder: " + finishOrder); } catch (IllegalPathStateException ipse) { System.out.println(ipse.getMessage()); } Output: dfsVisit(): cycle involving vertices D and E

Depth-First Search Algorithm Depth ‑ first search begins with all WHITE vertices and performs depth ‑ first visits until all vertices of the graph are BLACK. The algorithm returns a list of all vertices in the graph in the reverse order of their finishing times. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

dfs() // depth-first search; dfsList contains all // the graph vertices in the reverse order // of their finishing times public static void dfs(DiGraph g, LinkedList dfsList) { Iterator graphIter; T vertex = null; // clear dfsList dfsList.clear(); // initialize all vertices to WHITE g.colorWhite();

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. dfs() (concluded) // call dfsVisit() for each WHITE vertex graphIter = g.vertexSet().iterator(); while (graphIter.hasNext()) { vertex = graphIter.next(); if (g.getColor(vertex) == VertexColor.WHITE) dfsVisit(g, vertex, dfsList, false); }

Running Time for Depth-First Search An argument similar to that for the breadth- first search shows that that the running time for dfs() is O(V+E), where V is the number of vertices in the graph and E is the number of edges. © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved.

Depth-First Search Example © 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. dfsVisit() starting at E followed by dfsVisit() starting at A dfsList: [A, B, C, E, F, G, D]

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. Program 24.2 import java.io.FileNotFoundException; import ds.util.DiGraph; import ds.util.DiGraphs; public class Program24_2 { public static void main(String[] args) throws FileNotFoundException { DiGraph g = DiGraph.readGraph("cycle.dat"); // determine if the graph is acyclic if (DiGraphs.acyclic(g)) System.out.println("Graph is acyclic"); else System.out.println("Graph is not acyclic");

© 2005 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. Program 24.2 (concluded) // add edge (E,B) to create a cycle System.out.print(" Adding edge (E,B): "); g.addEdge("E", "B", 1); // retest the graph to see if it is acyclic if (DiGraphs.acyclic(g)) System.out.println("New graph is acyclic"); else System.out.println("New graph is not acyclic"); } Run: Graph is acyclic Adding edge (E,B): New graph is not acyclic

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The provided text passage discusses graph traversal algorithms, specifically focusing on breadth-first search (BFS) and depth-first search (DFS). It explains the concepts, processes, and running times of these algorithms, and provides examples of their implementation and usage.

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The passage does not contain any mathematical questions or problems that require solving. It is purely descriptive and explanatory in nature, providing information about graph traversal algorithms.