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
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[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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