Road three-dimensional linear automatic optimization method based on improved particle swarm optimization

A particle swarm algorithm and automatic optimization technology, which is applied in computing, special data processing applications, instruments, etc., can solve problems such as optimization and unprovided line selection

Inactive Publication Date: 2013-11-20
CENT SOUTH UNIV
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Problems solved by technology

However, the prior art does not provide a way to optimize the line selection of the plane and longitudinal sections of the line using GIS at the same time

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  • Road three-dimensional linear automatic optimization method based on improved particle swarm optimization
  • Road three-dimensional linear automatic optimization method based on improved particle swarm optimization
  • Road three-dimensional linear automatic optimization method based on improved particle swarm optimization

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Embodiment Construction

[0078] Below in conjunction with accompanying drawing and embodiment the present invention will be further described:

[0079] The present invention is an automatic optimization method for three-dimensional road alignment based on the improved particle swarm optimization algorithm. Firstly, the objective function for three-dimensional alignment optimization of the road is established, and the constraint conditions of the plane and longitudinal section of the road are set, the unit price of road construction, the distance between points taken by the road and the alignment optimization are set. In the target area, the improved particle swarm optimization algorithm is used to simultaneously optimize the parameters of the plane intersection point and the slope change point of the longitudinal section of the three-dimensional line shape obtained by using ArcGIS software to obtain the automatically optimized three-dimensional line shape of the road;

[0080] The plane intersection po...

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Abstract

The invention discloses a road three-dimensional linear automatic optimization method based on an improved particle swarm optimization. Firstly, a road three-dimensional linear optimization objective function is established, the improved particle swarm optimization is adopted to carry out optimization on the plane intersection point parameters of three-dimensional linetype and vertical section grade change point parameters of leading line scheme obtained by adopting ArcGIS software simultaneously according to the constraint conditions, the road construction unit price, the line point obtaining intervals and the linear optimization objective areas of set line planes and the vertical sections, and the road three-dimensional linear after automatic optimization is obtained. The three-dimensional linear after automatic optimization can pass around obstacles and be adapt to terrains better, is used as earlier stage design reference for project planners, and labor intensity of the project planners is reduced.

Description

technical field [0001] The invention relates to the field of route selection of roads or railways, in particular to an automatic optimization method for road three-dimensional alignment based on improved particle swarm algorithm. Background technique [0002] According to the basic direction and main technical standards of the railway (road) road, the purpose of automatic line selection is to realize the automatic design of the plane and longitudinal section of the railway or road at the same time. In the process of automatic route selection, it is necessary to find an optimal plan (usually the least economical cost) from multiple route plans that satisfy the constraint conditions. Since its objective function can only be obtained through digital elevation model interpolation and includes various costs, the function is usually non-differentiable. Since there are infinitely many route schemes satisfying the constraint conditions between the starting point and the end point, ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06Q10/04
Inventor 缪鹍周干姜伟罗枫田家凯杨柏林徐霞
Owner CENT SOUTH UNIV
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