Self-adaption quantum ant colony-based query method and device for railway traffic transfer plans

Abstract

The invention relates to a self-adaption quantum ant colony-based query method and a self-adaption quantum ant colony-based query device for railway traffic transfer plans. The method comprises the following steps of performing permission setting and database update setting on a query machine terminal by a management console through a management machine; starting the query machine terminal, receiving a query request by a touch screen, and sending the query request to a central processing module; building a multi-mode optimal path model by the central processing module according to the query request, executing a self-adaption quantum ant colony algorithm based on the multi-mode optimal path model, and working out optimal railway traffic transfer plans under different optimal targets; and judging whether optimization is ended or not, and feeding back a computed result to the touch screen if the optimization is ended. The device comprises the management console, the management machine and the query machine terminal. Compared with the prior art, the method and the device disclosed by the invention are capable of performing high-efficiency optimization design on the optimal transfer of a complicated national railway traffic network under the multi-constraint condition, and therefore, the flexibility and the high efficiency of passenger travelling to the railway traffic transfer can be improved.

Description

technical field [0001] The invention relates to a technology for querying an optimal transfer scheme of railway traffic, in particular to a method and device for querying a railway traffic transfer scheme based on an adaptive quantum ant colony. Background technique [0002] With the rapid development of our country's national economy, the level of national income continues to increase, the frequency of people's travel continues to increase, and a higher level of requirements has been placed on the transportation service industry. In summary, there are convenience, speed and safety in the travel process. A series of higher-quality full-services such as security, comfort, punctuality, economy and good service attitude. [0003] Generally speaking, railway passengers mainly travel in two ways: direct and transit. In this information age, passengers can easily check the main information such as the number of available trains, travel time, travel mileage and fare from the depar...

AI Technical Summary

Problems solved by technology

[0004] my country has a vast territory, and the construction of railway network is extremely complicated. At present, there are more than 5,000 railway passenger stations in the country. At the same time, the operation and large-scale construction of my country's high-speed railway will make my country's railway network more complicated. This is the passenger transfer service work of the railway department. The traditional shortest path algorithm cannot solve the large-scale multi-objective optimization problem, and the existing online train timetable provides all possible travel plans, without comprehensively considering the preferences of different types of passengers on different travel factors level, unable to provide targeted inquiry services

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