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Multi-path planning method based on improved particle swarm optimization

A technology for improving particle swarm and multi-path, applied in computing, data processing application, prediction and other directions, can solve problems such as precociousness, and achieve the effect of avoiding precociousness, good effect, and increasing range

Inactive Publication Date: 2014-09-24
HOHAI UNIV
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Problems solved by technology

This algorithm has the advantages of easy implementation, high precision, and fast convergence, but it still has the disadvantage of being easily trapped in a local optimal solution and leading to "premature".

Method used

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  • Multi-path planning method based on improved particle swarm optimization
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  • Multi-path planning method based on improved particle swarm optimization

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Embodiment Construction

[0015] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0016] 1. Traveling Salesman Problem (TSP)

[0017] TSP is to find the shortest path to traverse N cities, and its mathematical description is as follows:

[0018] Set C={c with N cities 1 ,c 2 ,...,c N}, the distance between every 2 cities is d(c i ,c j )∈R + Among them, c i ,c j ∈C(1≤i,j≤N) find the objective function T d =∑d(c ∏(i) ,c ∏(i+1) )+d(c ∏(N) ,c ∏(1) ) to achieve the smallest city sequence {c∏(1),c∏(2),...,c∏(N)}, where ∏(1),∏(2),...,∏(N) are The full permutation of 1,2,...

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Abstract

The invention discloses a multi-path planning method based on improved particle swarm optimization. The ideas of a greedy algorithm, a genetic algorithm and a simulated annealing algorithm are fused on the basis of the improvement on the particle swarm optimization for solving single-path panning, and the greedy algorithm is used for initializing the particle swarm optimization and an excellent mutation operator and the simulated annealing idea are added. The path calculated are considered as being connected end to end into a ring; for a multi-path problem of the same departure city, N virtual cities the same as the departure city in location are added for calculating N paths, and meeting the virtual city in the path represents returning to the departure city, and in this way, the ring is divided into N paths; for a multi-path problem of different departure cities, no virtual city needs to be added and all the departure cities function as the departure cities. The multi-path planning method is simpler and more universal than the previous methods.

Description

technical field [0001] The invention relates to a multi-path planning method based on an improved particle swarm algorithm. Background technique [0002] The multi-path planning problem, that is, the multi-traveling salesman problem is a generalization of the classic traveling salesman problem. With some specific additional conditions, it can evolve into some more realistic problems, so it has high theoretical research and application value. . In the multi-traveling salesman problem, a task is jointly completed by multiple traveling salesmen, and the problem is more difficult to solve than the classic traveling salesman problem. The methods or strategies used for solving the classic traveling salesman problem cannot be simply applied to the multi-traveling salesman problem The research results on this problem are far less than the classic traveling salesman problem. The existing method of calculating multi-path is to add virtual cities, separate all cities, and convert them...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04
Inventor 张雪洁严祥光周文欢蒋悦达
Owner HOHAI UNIV
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