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Maneuvering path optimization method and storage medium based on multi-habitat genetic algorithm

A genetic algorithm and path technology, applied in the field of maneuver path optimization modeling, can solve the problem of low algorithm efficiency, achieve the effect of reducing the amount of calculation, improving effectiveness and efficiency, and achieving ideal solution results

Active Publication Date: 2020-11-03
BEIJING HUARU TECH
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Problems solved by technology

[0005] However, the above algorithms are usually not efficient, and there are validity problems

Method used

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  • Maneuvering path optimization method and storage medium based on multi-habitat genetic algorithm
  • Maneuvering path optimization method and storage medium based on multi-habitat genetic algorithm
  • Maneuvering path optimization method and storage medium based on multi-habitat genetic algorithm

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Embodiment 1

[0049] see figure 2 , shows an optimal example of an agent path according to a specific embodiment of the present invention.

[0050] Problem analysis step S110: The single agent plans to start from node P00 at 8:00 with a speed of 56 km / h, and is required to arrive at adjustment node P15 (must pass point) before 9:40, and at 14:45 Before 18:25, reach the adjustment node P51 (necessary point), and before 18:25, reach the target node P80. It is required to combine the known path length L of each path segment (see Table 1), road condition coefficient K (see Table 2) and risk coefficient D (see Table 3) to optimize a reasonable maneuvering path for a single agent.

[0051] Table 1 Path length L of each path segment (unit: kilometer)

[0052]

[0053]

[0054] Table 2 Road Condition Coefficient K

[0055]

[0056] Table 3 Risk coefficient D

[0057]

[0058] Problem representation step S120: According to the known conditions of the problem to be solved, combined w...

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Abstract

A single agent mobile path optimization method based on a multi-niche genetic algorithm and a storage medium are disclosed. Aimint at the path optimization problem, the multi-niche genetic algorithm and the Dijkstra algorithm are used to raise problems and analyze problems; the multi-niche genetic algorithm is used to perform population initialization, multi-niche genetic algorithm computation, decoding and fitness calculation; the usage of Dijkstra algorithm is improved, In a small number of path groups, searching whether there are connected paths to achieve the single agent shortest path optimization problem in combat simulation, which significantly improves the effectiveness and efficiency of single agent path optimization under constrained conditions in the process of combat simulation, reduces the overall computational load, and efficiently obtains the optimal solution of the problem.

Description

technical field [0001] The invention relates to the field of computer simulation, in particular to a maneuver path optimization modeling method with agent modeling as the core and multi-habitat genetic algorithm and improved Dijkstra algorithm path optimization as key points. Background technique [0002] The problem of single-agent maneuver path optimization (hereinafter referred to as path optimization) is a typical complex combinatorial optimization problem. The problem of its research is described as: starting from the starting point of a single agent, there are n optional path nodes (referred to as nodes), and the distance between each node and the road condition coefficient ([0.0,1.0] are known. The larger the value, the better the road condition. Good), and the enemy situation risk coefficient between each node ([1.0,+∞), the smaller the value, the smaller the enemy situation risk). Starting from the starting point of a single agent, it is required to optimize an eff...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/12G06Q10/04
CPCG06N3/126G06Q10/047
Inventor 连广彦王军汤磊陆皓李大鹏高连峰
Owner BEIJING HUARU TECH
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