Shortest Path Search Method Based on Path and Weight

Abstract

The invention aims to provide a shortest route searching method based on a route and weight. The shortest route searching method comprises the following steps that (1) the length of route each road equals a value of a real distance dividing a weight value; (2) each road in a to-be-analyzed area is connected; (3) starting points and terminal points are connected to achieve connection lines, so a plurality of initial route polygons can be achieved; (4) the plurality of initial route polygons are combined to achieve a coated polygon; (5) with the connection lines as a border, a starting left route and a starting right route of the coated polygon can be achieved; (6) a shorter connection line is employed to replace a connection line of two points corresponding to the starting routes and search is orderly continued to achieved a new left route and a new right route; (7) if the new left route and the new right routes are overlapped, the overlapped part is sure to be the shortest route part; if the new left route and the new right route are not overlapped, a final left route and a final right route can be achieved; (8) middle polygons in the final left route and the final right route are combined to achieved a combined polygon; and (9) a public part of the new left and right routes is combined with an acquired result to achieve the final shortest route. The shortest route searching method based on route and weight has high searching efficiency and precision, and can be applied to current each space data processing software platforms.

Description

technical field [0001] The invention relates to the fields of mathematics and computer graphics, in particular to a search method for the shortest path based on path and weight. Background technique [0002] The shortest path search commonly includes Dijkstra algorithm (single-source shortest path), Floyd algorithm (interpolation method), AStar algorithm (heuristic shortest path algorithm), etc., among which the most famous algorithm is Djikstra algorithm. The implementation of this algorithm is based on the adjacency matrix representation of the graph. It can not only find the shortest path between any two points, but also find the shortest path from a specified point to all other vertices. Although the Dijkstra algorithm is simple, it needs to search all paths within the range. If the number of nodes in the network is very large, the calculation efficiency will drop sharply. The advantage of the Floyd algorithm is that the initial conditions are proposed, which avoids the...

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Problems solved by technology

[0003] Although the above methods can realize the shortest path search problem, they have the following disadvantages and deficiencies: 1) The search efficiency is low, and it is difficult to balance the search results and efficiency; 2) The processing process is complicated, and although the algorithm is mature, it fails to combine the spatial relationship to improve the search efficiency and accuracy; 3) The road conditions are different. The current shortest path search algorithm considers the geometric shortest path more, and rarely updates the shortest path dynamically and in real time according to the road conditions and needs to search again

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