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Research On Optimizing The Layout Of Parking Sites For Shared Bicycles

Posted on:2020-08-08Degree:MasterType:Thesis
Country:ChinaCandidate:C Y ZhaoFull Text:PDF
GTID:2392330626450440Subject:Traffic and Transportation Engineering
Abstract/Summary:PDF Full Text Request
In recent years,the parking problem of shared bicycles has been relatively prominent.With the corresponding renovation policies for shared bicycle parking in major cities throughout the country,it is of great theoretical and practical significance to study the layout optimization of parking points.Firstly,the data of shared bicycle riding is preprocessed,and the characteristics of travel time,travel space and travel intensity of shared bicycle are deeply analyzed using the data after processing.At the same time,the identification method of shared bicycle demand points is proposed to support the follow-up research.Secondly,by introducing DSR model to evaluate the supply of shared bicycle parking points,the evaluation index system of shared bicycle parking points supply is constructed by analytic hierarchy process.By combining the two weights,each index can be weighted.Finally,the relative closeness degree of Topsis evaluation method is introduced to rank the evaluation results and determine the alternative points of shared bicycle parking points.Thirdly,a multi-objective programming model for the layout optimization of shared bicycle parking points is established,which takes the alternative points as the object of layout optimization and considers many scenarios such as coverage,time satisfaction,service timeliness and demand uncertainty.The model is solved by software.Finally,the study case area is determined,and the shared bicycle demand points are identified by clustering method.The initial available parking points around the demand points are evaluated by the evaluation index system,and the set of alternative points is determined.Finally,the layout optimization model is solved and the results are analyzed.
Keywords/Search Tags:shared bicycle, demand point identification, combination weighting, robustness
PDF Full Text Request
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