Method and system for determining optimal path based on quantum genetic algorithm, and medium

Abstract

The invention provides a method and a system for determining an optimal path based on a quantum genetic algorithm, and a medium. Performing quantum coding on all the paths to generate a quantum population containing a plurality of chromosomes, and initializing all the paths subjected to quantum coding to enable genes on all the chromosomes in the quantum population to have the same initial probability; calculating the fitness of each path in all the paths according to the initial probability, and selecting a first fitness; on the basis of the first fitness, performing first optimization on all paths subjected to quantum coding by using a corrected quantum revolving door, including evolving a quantum population to obtain a new generation of quantum population; second optimization is executed on all the paths after the first optimization is completed, the second optimization is chromosome cross optimization, and new first fitness is selected; and determining the new first fitness as the first fitness, and outputting a path corresponding to the new first fitness as an optimal path.

Description

technical field [0001] The present disclosure relates to the field of quantum computing, in particular to a method, system and medium for determining an optimal path based on a quantum genetic algorithm. Background technique [0002] The combination of quantum mechanics and modern information computing has two important branches, one is the physical realization of quantum computing platforms, and the other important direction is the exploration of quantum algorithms. Since the quantum algorithm of prime factorization of large numbers was proposed in 1994, the research on quantum algorithms has been widely used in neural networks, intelligent control, complex optimization and other fields. At the same time, quantum algorithms have been developed into more and more classical algorithms, such as genetic algorithm, particle swarm algorithm and so on. [0003] Quantum genetic algorithm is a probability-optimized search algorithm that uses qubits to encode chromosomes and uses qu...

AI Technical Summary

Problems solved by technology

If the value is too large, the convergence speed will be slowed down, and if the value is too small, the chromosome will end its evolution before finding the optimal solution. Therefore, the evolution method of the quantum revolving door with fixed angle cannot satisfy the actual optimization process.

When determining the optimal path, it seriously affects the accuracy of the optimal path and the planning time

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