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Path optimization method

A path optimization and path technology, applied in data processing applications, forecasting, computing, etc., can solve problems such as unsatisfactory computing effect, large computing scale, and long computing time, so as to achieve short computing time, good computing effect, and reduce computing time. effect of time

Inactive Publication Date: 2015-04-29
SHANXI UNIV
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Problems solved by technology

In the actual application process, if the complexity of the path and multi-combination constraints are considered, when the number of destinations is relatively large, the calculation scale of the problem will become very large. Traditional greedy algorithms, Monte Carlo algorithms, neural networks, etc. Network algorithms, etc., will face problems such as increased calculation scale and longer calculation time, resulting in unsatisfactory calculation results.

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Embodiment Construction

[0019] (1) In the first stage, the adjacency matrix of the distance between each point is constructed by combining the constraints of the intersection points

[0020] ① Connectivity processing of intersections, departure points, destinations, etc.

[0021] In scientific computing and logistics distribution problems, no matter the starting point or the destination point is always composed of many path connections, and the path is composed of the most basic element of intersection; in order to calculate the path accurately, considering the constraints of the intersection, first construct A system for describing intersection connectivity;

[0022] Taking the logistics problem as an example, the intersections and roads in real life constitute the basic elements connecting the starting point and the destination point. Each intersection has some constraints (for example: traffic lights at the intersection, whether U-turns and left-turn lights are allowed);

[0023] The representat...

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Abstract

The invention discloses a path optimization method. The method is characterized in that the best and shortest path of large-scale destinations is calculated by a simulated annealing algorithm. According to the method and the system, the calculation time can be obviously shortened, and thus the method is relatively high in practicability and can be applied to cold atom dynamics and quantum phase transition calculation in an optical lattice, logistics distribution and other fields. The method can be applied to cold atom dynamics and quantum phase transition calculation in an optical lattice, logistics distribution and other fields, according to a three-level process algorithm, the calculation time can be obviously shortened, and thus the method is relatively high in practicability. In particular for calculation of large-scale destinations, the method is very short in calculation time and excellent in calculation effect, and thus the method is almost the unique feasible processing method.

Description

technical field [0001] The invention is a path optimization method, which mainly uses a simulated annealing algorithm to calculate the shortest and optimal path of large-scale destinations. By adopting the method and system, the calculation time can be significantly reduced, and the utility model has extremely high practicability, and can be applied to scientific calculation, logistics distribution and other fields. Background technique [0002] In scientific computing and daily life (such as logistics and distribution problems), it is often calculated to start from a certain location, return through multiple destinations, and optimize the problem of obtaining the shortest path. In the actual application process, if the complexity of the path and multi-combination constraints are considered, when the number of destinations is relatively large, the calculation scale of the problem will become very large. Traditional greedy algorithms, Monte Carlo algorithms, neural networks, ...

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Application Information

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IPC IPC(8): G06Q10/04
CPCG06Q10/047
Inventor 杜磊郭利平耿彦峰李雪莲王晋平
Owner SHANXI UNIV
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