Dijkstraov algoritmus

Dijkstraov algoritmus nám umožňuje nájsť najkratšiu cestu medzi dvoma vrcholmi grafu.

Líši sa od minimálneho rozloženého stromu, pretože najkratšia vzdialenosť medzi dvoma vrcholmi nemusí zahŕňať všetky vrcholy grafu.

Ako funguje Dijkstraov algoritmus

Dijkstraov algoritmus pracuje na základe toho, že akákoľvek podcesta B -> Dnajkratšej cesty A -> Dmedzi vrcholmi A a D je zároveň najkratšou cestou medzi vrcholmi B a D.

Každá čiastková cesta je najkratšou cestou

Djikstra túto vlastnosť použil v opačnom smere, tj. Preceňujeme vzdialenosť každého vrcholu od východiskového. Potom navštívime každý uzol a jeho susedov, aby sme našli najkratšiu cestu k týmto susedom.

Algoritmus používa nenásytný prístup v tom zmysle, že nájdeme ďalšie najlepšie riešenie v nádeji, že konečný výsledok bude najlepším riešením pre celý problém.

Príklad Dijkstraovho algoritmu

Je jednoduchšie začať príkladom a potom premýšľať o algoritme.

Začnite s váženým grafom Vyberte počiatočný vrchol a priraďte hodnoty cesty nekonečna všetkým ostatným zariadeniam Prejdite ku každému vrcholu a aktualizujte jeho dĺžku cesty Ak je dĺžka cesty susedného vrcholu menšia ako dĺžka novej cesty, neaktualizujte ju Vyvarujte sa aktualizácii cesty dĺžky už navštívených vrcholov Po každej iterácii vyberieme nenavštívený vrchol s najmenšou dĺžkou cesty. Vyberieme teda 5 pred 7 Všimnite si, ako má vrchol pravej strany dvakrát aktualizovanú dĺžku svojej cesty Opakujte, kým nebudú navštívené všetky vrcholy

Djikstraov algoritmus pseudokód

Musíme zachovať dráhovú vzdialenosť každého vrcholu. Môžeme to uložiť do poľa veľkosti v, kde v je počet vrcholov.

Chceme tiež mať možnosť dostať sa na najkratšiu cestu, nielen poznať dĺžku najkratšej cesty. Za týmto účelom mapujeme každý vrchol na vrchol, ktorý naposledy aktualizoval svoju dĺžku cesty.

Po dokončení algoritmu môžeme nájsť cestu späť z cieľového vrcholu do zdrojového.

Na efektívne prijatie vrcholu s najmenšou vzdialenosťou dráhy je možné použiť front s minimálnou prioritou.

 function dijkstra(G, S) for each vertex V in G distance(V) <- infinite previous(V) <- NULL If V != S, add V to Priority Queue Q distance(S) <- 0 while Q IS NOT EMPTY U <- Extract MIN from Q for each unvisited neighbour V of U tempDistance <- distance(U) + edge_weight(U, V) if tempDistance < distance(V) distance(V) <- tempDistance previous(V) <- U return distance(), previous()

Kód pre Dijkstraov algoritmus

Ďalej je uvedená implementácia Dijkstraovho algoritmu v jazyku C ++. Zložitosť kódu sa dá vylepšiť, ale abstrakcie sú vhodné na spojenie kódu s algoritmom.

Python Java C C ++
 # Dijkstra's Algorithm in Python import sys # Providing the graph vertices = ((0, 0, 1, 1, 0, 0, 0), (0, 0, 1, 0, 0, 1, 0), (1, 1, 0, 1, 1, 0, 0), (1, 0, 1, 0, 0, 0, 1), (0, 0, 1, 0, 0, 1, 0), (0, 1, 0, 0, 1, 0, 1), (0, 0, 0, 1, 0, 1, 0)) edges = ((0, 0, 1, 2, 0, 0, 0), (0, 0, 2, 0, 0, 3, 0), (1, 2, 0, 1, 3, 0, 0), (2, 0, 1, 0, 0, 0, 1), (0, 0, 3, 0, 0, 2, 0), (0, 3, 0, 0, 2, 0, 1), (0, 0, 0, 1, 0, 1, 0)) # Find which vertex is to be visited next def to_be_visited(): global visited_and_distance v = -10 for index in range(num_of_vertices): if visited_and_distance(index)(0) == 0 and (v < 0 or visited_and_distance(index)(1) <= visited_and_distance(v)(1)): v = index return v num_of_vertices = len(vertices(0)) visited_and_distance = ((0, 0)) for i in range(num_of_vertices-1): visited_and_distance.append((0, sys.maxsize)) for vertex in range(num_of_vertices): # Find next vertex to be visited to_visit = to_be_visited() for neighbor_index in range(num_of_vertices): # Updating new distances if vertices(to_visit)(neighbor_index) == 1 and visited_and_distance(neighbor_index)(0) == 0: new_distance = visited_and_distance(to_visit)(1) + edges(to_visit)(neighbor_index) if visited_and_distance(neighbor_index)(1)> new_distance: visited_and_distance(neighbor_index)(1) = new_distance visited_and_distance(to_visit)(0) = 1 i = 0 # Printing the distance for distance in visited_and_distance: print("Distance of ", chr(ord('a') + i), " from source vertex: ", distance(1)) i = i + 1
 // Dijkstra's Algorithm in Java public class Dijkstra ( public static void dijkstra(int()() graph, int source) ( int count = graph.length; boolean() visitedVertex = new boolean(count); int() distance = new int(count); for (int i = 0; i < count; i++) ( visitedVertex(i) = false; distance(i) = Integer.MAX_VALUE; ) // Distance of self loop is zero distance(source) = 0; for (int i = 0; i < count; i++) ( // Update the distance between neighbouring vertex and source vertex int u = findMinDistance(distance, visitedVertex); visitedVertex(u) = true; // Update all the neighbouring vertex distances for (int v = 0; v < count; v++) ( if (!visitedVertex(v) && graph(u)(v) != 0 && (distance(u) + graph(u)(v) < distance(v))) ( distance(v) = distance(u) + graph(u)(v); ) ) ) for (int i = 0; i < distance.length; i++) ( System.out.println(String.format("Distance from %s to %s is %s", source, i, distance(i))); ) ) // Finding the minimum distance private static int findMinDistance(int() distance, boolean() visitedVertex) ( int minDistance = Integer.MAX_VALUE; int minDistanceVertex = -1; for (int i = 0; i < distance.length; i++) ( if (!visitedVertex(i) && distance(i) < minDistance) ( minDistance = distance(i); minDistanceVertex = i; ) ) return minDistanceVertex; ) public static void main(String() args) ( int graph()() = new int()() ( ( 0, 0, 1, 2, 0, 0, 0 ), ( 0, 0, 2, 0, 0, 3, 0 ), ( 1, 2, 0, 1, 3, 0, 0 ), ( 2, 0, 1, 0, 0, 0, 1 ), ( 0, 0, 3, 0, 0, 2, 0 ), ( 0, 3, 0, 0, 2, 0, 1 ), ( 0, 0, 0, 1, 0, 1, 0 ) ); Dijkstra T = new Dijkstra(); T.dijkstra(graph, 0); ) )
 // Dijkstra's Algorithm in C #include #define INFINITY 9999 #define MAX 10 void Dijkstra(int Graph(MAX)(MAX), int n, int start); void Dijkstra(int Graph(MAX)(MAX), int n, int start) ( int cost(MAX)(MAX), distance(MAX), pred(MAX); int visited(MAX), count, mindistance, nextnode, i, j; // Creating cost matrix for (i = 0; i < n; i++) for (j = 0; j < n; j++) if (Graph(i)(j) == 0) cost(i)(j) = INFINITY; else cost(i)(j) = Graph(i)(j); for (i = 0; i < n; i++) ( distance(i) = cost(start)(i); pred(i) = start; visited(i) = 0; ) distance(start) = 0; visited(start) = 1; count = 1; while (count < n - 1) ( mindistance = INFINITY; for (i = 0; i < n; i++) if (distance(i) < mindistance && !visited(i)) ( mindistance = distance(i); nextnode = i; ) visited(nextnode) = 1; for (i = 0; i < n; i++) if (!visited(i)) if (mindistance + cost(nextnode)(i) < distance(i)) ( distance(i) = mindistance + cost(nextnode)(i); pred(i) = nextnode; ) count++; ) // Printing the distance for (i = 0; i < n; i++) if (i != start) ( printf("Distance from source to %d: %d", i, distance(i)); ) ) int main() ( int Graph(MAX)(MAX), i, j, n, u; n = 7; Graph(0)(0) = 0; Graph(0)(1) = 0; Graph(0)(2) = 1; Graph(0)(3) = 2; Graph(0)(4) = 0; Graph(0)(5) = 0; Graph(0)(6) = 0; Graph(1)(0) = 0; Graph(1)(1) = 0; Graph(1)(2) = 2; Graph(1)(3) = 0; Graph(1)(4) = 0; Graph(1)(5) = 3; Graph(1)(6) = 0; Graph(2)(0) = 1; Graph(2)(1) = 2; Graph(2)(2) = 0; Graph(2)(3) = 1; Graph(2)(4) = 3; Graph(2)(5) = 0; Graph(2)(6) = 0; Graph(3)(0) = 2; Graph(3)(1) = 0; Graph(3)(2) = 1; Graph(3)(3) = 0; Graph(3)(4) = 0; Graph(3)(5) = 0; Graph(3)(6) = 1; Graph(4)(0) = 0; Graph(4)(1) = 0; Graph(4)(2) = 3; Graph(4)(3) = 0; Graph(4)(4) = 0; Graph(4)(5) = 2; Graph(4)(6) = 0; Graph(5)(0) = 0; Graph(5)(1) = 3; Graph(5)(2) = 0; Graph(5)(3) = 0; Graph(5)(4) = 2; Graph(5)(5) = 0; Graph(5)(6) = 1; Graph(6)(0) = 0; Graph(6)(1) = 0; Graph(6)(2) = 0; Graph(6)(3) = 1; Graph(6)(4) = 0; Graph(6)(5) = 1; Graph(6)(6) = 0; u = 0; Dijkstra(Graph, n, u); return 0; )
 // Dijkstra's Algorithm in C++ #include #include #define INT_MAX 10000000 using namespace std; void DijkstrasTest(); int main() ( DijkstrasTest(); return 0; ) class Node; class Edge; void Dijkstras(); vector* AdjacentRemainingNodes(Node* node); Node* ExtractSmallest(vector& nodes); int Distance(Node* node1, Node* node2); bool Contains(vector& nodes, Node* node); void PrintShortestRouteTo(Node* destination); vector nodes; vector edges; class Node ( public: Node(char id) : id(id), previous(NULL), distanceFromStart(INT_MAX) ( nodes.push_back(this); ) public: char id; Node* previous; int distanceFromStart; ); class Edge ( public: Edge(Node* node1, Node* node2, int distance) : node1(node1), node2(node2), distance(distance) ( edges.push_back(this); ) bool Connects(Node* node1, Node* node2) ( return ( (node1 == this->node1 && node2 == this->node2) || (node1 == this->node2 && node2 == this->node1)); ) public: Node* node1; Node* node2; int distance; ); /////////////////// void DijkstrasTest() ( Node* a = new Node('a'); Node* b = new Node('b'); Node* c = new Node('c'); Node* d = new Node('d'); Node* e = new Node('e'); Node* f = new Node('f'); Node* g = new Node('g'); Edge* e1 = new Edge(a, c, 1); Edge* e2 = new Edge(a, d, 2); Edge* e3 = new Edge(b, c, 2); Edge* e4 = new Edge(c, d, 1); Edge* e5 = new Edge(b, f, 3); Edge* e6 = new Edge(c, e, 3); Edge* e7 = new Edge(e, f, 2); Edge* e8 = new Edge(d, g, 1); Edge* e9 = new Edge(g, f, 1); a->distanceFromStart = 0; // set start node Dijkstras(); PrintShortestRouteTo(f); ) /////////////////// void Dijkstras() ( while (nodes.size()> 0) ( Node* smallest = ExtractSmallest(nodes); vector* adjacentNodes = AdjacentRemainingNodes(smallest); const int size = adjacentNodes->size(); for (int i = 0; i at(i); int distance = Distance(smallest, adjacent) + smallest->distanceFromStart; if (distance distanceFromStart) ( adjacent->distanceFromStart = distance; adjacent->previous = smallest; ) ) delete adjacentNodes; ) ) // Find the node with the smallest distance, // remove it, and return it. Node* ExtractSmallest(vector& nodes) ( int size = nodes.size(); if (size == 0) return NULL; int smallestPosition = 0; Node* smallest = nodes.at(0); for (int i = 1; i distanceFromStart distanceFromStart) ( smallest = current; smallestPosition = i; ) ) nodes.erase(nodes.begin() + smallestPosition); return smallest; ) // Return all nodes adjacent to 'node' which are still // in the 'nodes' collection. vector* AdjacentRemainingNodes(Node* node) ( vector* adjacentNodes = new vector(); const int size = edges.size(); for (int i = 0; i node1 == node) ( adjacent = edge->node2; ) else if (edge->node2 == node) ( adjacent = edge->node1; ) if (adjacent && Contains(nodes, adjacent)) ( adjacentNodes->push_back(adjacent); ) ) return adjacentNodes; ) // Return distance between two connected nodes int Distance(Node* node1, Node* node2) ( const int size = edges.size(); for (int i = 0; i Connects(node1, node2)) ( return edge->distance; ) ) return -1; // should never happen ) // Does the 'nodes' vector contain 'node' bool Contains(vector& nodes, Node* node) ( const int size = nodes.size(); for (int i = 0; i < size; ++i) ( if (node == nodes.at(i)) ( return true; ) ) return false; ) /////////////////// void PrintShortestRouteTo(Node* destination) ( Node* previous = destination; cout << "Distance from start: "  id 
 node2 == node) ( cout << "adjacent: "  id 
   

Dijkstra's Algorithm Complexity

Time Complexity: O(E Log V)

where, E is the number of edges and V is the number of vertices.

Space Complexity: O(V)

Dijkstra's Algorithm Applications

  • To find the shortest path
  • In social networking applications
  • In a telephone network
  • To find the locations in the map

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