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The k shortest path routing problem is a generalization of the shortest path routing problem in a given network. It asks not only about a shortest path but also about next k−1 shortest paths (which may be longer than the shortest path). A variation of the problem is the loopless k shortest paths.
In graph theory and theoretical computer science, the longest path problem is the problem of finding a simple path of maximum length in a given graph.A path is called simple if it does not have any repeated vertices; the length of a path may either be measured by its number of edges, or (in weighted graphs) by the sum of the weights of its edges.
A 1999 study of the Stony Brook University Algorithm Repository showed that, out of 75 algorithmic problems related to the field of combinatorial algorithms and algorithm engineering, the knapsack problem was the 19th most popular and the third most needed after suffix trees and the bin packing problem.
A common example of a graph-based pathfinding algorithm is Dijkstra's algorithm. [3] This algorithm begins with a start node and an "open set" of candidate nodes. At each step, the node in the open set with the lowest distance from the start is examined.
Dijkstra's algorithm (/ ˈ d aɪ k s t r ə z / DYKE-strəz) is an algorithm for finding the shortest paths between nodes in a weighted graph, which may represent, for example, a road network. It was conceived by computer scientist Edsger W. Dijkstra in 1956 and published three years later.
The following table lists algorithms for solving the maximum flow problem. Here, V {\displaystyle V} and E {\displaystyle E} denote the number of vertices and edges of the network. The value U {\displaystyle U} refers to the largest edge capacity after rescaling all capacities to integer values (if the network contains irrational capacities, U ...
The undirected route inspection problem can be solved in polynomial time by an algorithm based on the concept of a T-join.Let T be a set of vertices in a graph. An edge set J is called a T-join if the collection of vertices that have an odd number of incident edges in J is exactly the set T.
The performance of users' solutions is evaluated based on execution speed and memory usage, and is ranked against other submissions in the LeetCode database. [6] Additionally, LeetCode provides its users with mock interviews and online assessments. LeetCode hosts weekly and biweekly contests, each having 4 problems.