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Shortest path problem. In graph theory, the shortest path problem is the problem of finding a path between two vertices (or nodes) in a graph such that the sum of the weights of its constituent edges is minimized. The problem of finding the shortest path between two intersections on a road map may be modeled as a special case of the shortest ...
A plot of walking speed versus slope resulting from Naismith's rule and Langmuir corrections for base speeds of 5 km/h and 4 km/h compared to Tobler's hiking function. Scarf's equivalence between distance and climb. Alternatively, the rule can be used to determine the equivalent flat distance of a route.
If a ship is using 1 g constant acceleration, it will appear to get near the speed of light in about a year, and have traveled about half a light year in distance. For the middle of the journey the ship's speed will be roughly the speed of light, and it will slow down again to zero over a year at the end of the journey.
A* search algorithm. A* (pronounced "A-star") is a graph traversal and pathfinding algorithm, which is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. [1] Given a weighted graph, a source node and a goal node, the algorithm finds the shortest path (with respect to the given weights) from ...
In graph algorithms, the widest path problem is the problem of finding a path between two designated vertices in a weighted graph, maximizing the weight of the minimum-weight edge in the path. The widest path problem is also known as the maximum capacity path problem. It is possible to adapt most shortest path algorithms to compute widest paths ...
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