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Research On Reginal Dispatch Of Public Transprortation

Posted on:2008-12-15Degree:MasterType:Thesis
Country:ChinaCandidate:H FangFull Text:PDF
GTID:2132360245478240Subject:Computer application technology
Abstract/Summary:PDF Full Text Request
With the development of world urbanization, the urban traffic problem, which is more severe and universal, has affected the life of every urban. It becomes urgent to be solved. The single-route model is generally applied by bus operators in China. Unfortunately, this model has limited both the efficiency of applying the currently insufficient resources and the potential of applying new techniques. Bus mufti-routes model is one scheduling method that resolves the problem about that vehicles are short in rush hours and leave unused in other hours, so to achieve information resource and transport ability sharing. The problem solved mainly in this thesis is how to utilize the genetic algorithm to solve the time interval of optimizing which modal is mufti-routes model.This paper has described the present intelligent traffic systematic background at first, then has described the question existing in the public transit dispatcher in detail, And has studied the present public transit dispatcher's methods.Secondly, with the service objective of multi-line regional scheduling, the paper provides the regional scheduling dispatch schedule simultaneously, which aim is the overall optimal society benefit. This paper also has appeared with the detailed course of asking a degree of models of demodulation of genetic algorithm, Have constructed the code way to accord with law of driving a vehicle, genetic algorithm and adapting to a degree of function. And taking two lines as an example, the model is tested.Lastly, this paper puts the method that genetic algorithm based on solution of bus regional scheduling into practice, processes use case and class design according to the software development, and implements the system under C# integrated development environment.
Keywords/Search Tags:regional scheduling, genetic algorithm, bus dispatch, modeling
PDF Full Text Request
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