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Dijkstra's algorithm uses a data structure for storing and querying partial solutions sorted by distance from the start. Dijkstra's original algorithm does not use a min-priority queue and runs in time Θ ( | V | 2 ) {\displaystyle \Theta (|V|^{2})}(where | V | {\displaystyle |V|} is the number of nodes).[10] The idea of this algorithm is also given in Leyzorek et al. 1957. Fredman & Tarjan 1984 propose using a Fibonacci heap min-priority queue to optimize the running time complexity to Θ ( | E | + | V | log ⁡ | V | )

The Dijkstra algorithm uses labels that are positive integers or real numbers, which are totally ordered. It can be generalized to use any labels that are partially ordered, provided the subsequent labels (a subsequent label is produced when traversing an edge) are monotonically non-decreasing. This generalization is called the generic Dijkstra shortest-path algorithm.[8][9]

For a given source node in the graph, the algorithm finds the shortest path between that node and every other.[7]: 196–206  It can also be used for finding the shortest paths from a single node to a single destination node by stopping the algorithm once the shortest path to the destination node has been determined. For example, if the nodes of the graph represent cities and costs of edge paths represent driving distances between pairs of cities connected by a direct road (for simplicity, ignore red lights, stop signs, toll roads and other obstructions), then Dijkstra's algorithm can be used to find the shortest route between one city and all other cities. A widely used application of shortest path algorithms is network routing protocols, most notably IS-IS (Intermediate System to Intermediate System) and OSPF (Open Shortest Path First). It is also employed as a subroutine in other algorithms such as Johnson's.