Searching method of fuzzy shortest path

A shortest path and fuzzy technology, applied in gene models, special data processing applications, instruments, etc., can solve the problems of shortest path search uncertainty, fuzzy uncertainty, difficulty in satisfying the generality of fuzzy shortest path search, etc., to meet Fuzzy Shortest Path Finding Versatility and Avoiding Limitations

Inactive Publication Date: 2010-06-23
SHANGHAI DIANJI UNIV
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Problems solved by technology

However, with the increase of the scale of the transportation network, the set of non-dominant paths is also increasing, and it is difficult for travelers to choose a better path from a large number of non-dominant paths, thus reducing the travel efficiency of travelers.
For the second method, because special fuzzy numbers are used to represent the weights of arcs in the network, and the characteristics of triangular fuzzy numbers are used, the weights of arcs in the network are triangular fuzzy numbers, and the length of any path connecting the starting point to the end point is still is a triangular fuzzy number, but if the weight of the arc is represented by other fuzzy numbers, the length of any path connecting the starting

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  • Searching method of fuzzy shortest path
  • Searching method of fuzzy shortest path
  • Searching method of fuzzy shortest path

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Embodiment

[0076] Such as Figure 5 and Figure 6 As shown, the shortest path search method based on fuzzy simulation genetic algorithm is applied to search for the shortest path for a fuzzy network with 10 nodes. The implementation process is as follows:

[0077] Step1: Initialize the number of chromosomes Pop-Size, crossover probability P c , the mutation probability P m .

[0078] Let Pop_Size=10, P c =0.8,P m = 0.3.

[0079] Step2: Generate Pop_Size chromosomes according to the encoding method of the priority.

[0080] Step3: Use fuzzy simulation to calculate the target value of all chromosomes, that is, satisfy the smallest

[0081] Step4: According to the target value, calculate the fitness of each chromosome and keep the value The smallest chromosome, denoted as v 0 , v 0 called the best chromosome.

[0082] Step5: Select chromosomes by gambling wheel to get a new population.

[0083] Step6: Perform crossover and mutation operations on the new population.

[0084...

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Abstract

The method of the invention analyzes a fuzzy shortest path from a new angle, introduces the reliability theory into the problem of the fuzzy shortest path, performs the characteristics that creditability measure has self-duality, truly represents the establishment of a fuzzy event and overcomes the deficiency of the possibility theory. Meanwhile, the invention overcomes the problem that the shortest path is hard to choose because of large traffic network scale and numerous non-dominant paths, puts forward an alpha-shortest path for the first time and designs a searching method of the shortest path on the basis of the fuzzy simulated genetic algorithm. In the method, the weight number of the arc in the network can be arbitrary fuzzy number, avoids the boundedness of the special fuzzy number and can satisfy the requirements of fuzzy shortest path searching generality.

Description

technical field [0001] The invention relates to a search method for the shortest path in a fuzzy network. Background technique [0002] In real life, some networks are often encountered, and the weight values ​​of all arcs are uncertain, and they are no longer clear values, but fuzzy. The weights of arcs in the network are described by fuzzy variables, and the fuzzy variables obey the distribution of membership functions. Such a network is called a fuzzy network. Fuzzy network has very important application value in real life. For example, the time delay analysis of communication network, the shortest path of urban traffic, the key road in operation planning, the head loss of water pipeline network damaged by earthquake damage, etc., which means that the length of the network link is usually uncertain and ambiguous . At present, there are two methods for finding the fuzzy shortest path: one is to find out the non-dominant path or Pareto optimal path set for travelers to c...

Claims

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Application Information

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IPC IPC(8): G06F17/50G06N3/12
Inventor 宁建红
Owner SHANGHAI DIANJI UNIV
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