Matrix compression algorithm for calculating shortest path of expressway

Abstract

The invention discloses a matrix compression algorithm for calculating the shortest path of an expressway. The matrix compression algorithm comprises the following steps of: 1, calculating a matrix graph of the path with the minimum cost of the expressway by using a Dijkstra algorithm; 2, performing matrix row compression, establishing a row tag array Flag [N] (initialized as full false), traversing a preorder matrix row by row, and compressing each row in the Pre array into a two-tuple set RowListi (column number c, value v); 3, matrix column compression: traversing the matrix column by column, compressing each column in the Pre array into a triple set ColListk (a starting value s, an end value e and a value v), and compressing and neglecting special points and repeated points in the matrix; and 4, completing matrix compression, and compressing the preorder array through a matrix compression algorithm, so that the required memory is greatly reduced, and the retrieval efficiency is not reduced too much.

Description

technical field [0001] The invention relates to the technical field of expressway algorithms, in particular to a matrix compression algorithm for expressway shortest path calculation. Background technique [0002] At present, the calculation of the minimum cost path of the expressway is based on the Dijkstra algorithm. The Dijkstra algorithm is to calculate the shortest path algorithm from one vertex to the other vertices, and it solves the problem of the shortest path in the weighted graph. . The main calculation process of Dijkstra's algorithm is to adopt the strategy of greedy algorithm. Starting from the starting point, each time it traverses the adjacent nodes of the vertices that are the closest to the starting point and have never been visited, until it reaches the end point. [0003] A brief highway network such as figure 2 As shown, it can be modeled in the following way: toll gates and toll gate entrances and toll gate exits of the highway as points in the direct...

AI Technical Summary

Problems solved by technology

[0037] The space complexity of the current technical solution is O(n2), and the main memory footprint is the preorder array Pre [N][N] , N is the number of midpoints in expressway network modeling, and the value of the total number of toll gates + total number of toll stations in the country is about 50000. The minimum memory space required by this technical solution is 10GB (50000*50000*4Byte), The size of this memory space is much larger than the memory size that the toll gantry system can provide, so this technical solution cannot meet the requirement of putting the minimum cost calculation on the toll gantry system

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