Hybrid quantum algorithm-based intelligent vehicle dispatching management system and working method thereof

Abstract

The invention discloses a hybrid quantum algorithm-based intelligent vehicle dispatching management system and a working method thereof. According to the system and the method, a hybrid quantum particle swarm optimization algorithm is disclosed through dividing a quantum particle swarm into two sub-phase particle swarms according to features of an optimization variable on the basis of using an improved quantum algorithm and an improved particle swarm algorithm; an elite quantum mean value and chaotic disturbance theory combined quantum evolution algorithm is designed on the basis of deeply researching advantages and boundedness of a tabu search algorithm in problem solution; and a simulated annealing algorithm and quantum algorithm combined hybrid quantum optimization algorithm is disclosed to solve demand-uncertain vehicle path problems; and a target function and a constraint condition of a dynamic vehicle path problem model are given. Simulated analysis results indicate that the method is capable of improving the convergence speed and convergence reliability, and is an effective method for solving demand-uncertain vehicle path problems.

Description

technical field [0001] The invention relates to a platform and a method of an intelligent vehicle dispatching management system, in particular to a platform and a method of an intelligent vehicle dispatching system based on hybrid quantum algorithm technology, belonging to the technical field of intelligent computing technology and Internet application management. Background technique [0002] With the rapid development of the world economy and the rapid progress of science and technology, the logistics industry has gradually developed into an important basic industry of the national economy. Vehicle routing problem (Vehicle Routing Problem, VRP), as a key link in the transportation and distribution system, has become one of the focus of attention, and has become a classic optimization combination problem in the field of operations research, and has also attracted attention from network analysis, applied mathematics and graph theory. The research interests of experts in othe...

AI Technical Summary

Problems solved by technology

[0004] (1) For uncertain VRP with a time window, there are many models studied, but the research points are relatively single, and the constraints in practical problems are often uncertain. Various uncertain factors such as vehicles, customer needs, and road condition information are comprehensively considered. issues that require further research

[0005] (2) For VRP with simultaneous set delivery, when the scale of the problem is large, the solution efficiency of the existing methods decreases significantly or even stagnates

[0006] (3) Most of the problems solved by the existing algorithms are limited to the case of clear information, and the specific change factors of the customer and the traffic environment, such as the specific location of the customer point, the importance of the customer, the smoothness of the road condition over time, etc. consider

Images