Study On The Location Decision And Scheduling Of City Public Bicycle’s Rental Station Model

Along with traffic mechanization brings a series of problems and the growingclimate issues, establish public bike system and encourage more travelers using thenon-motorized travel way, is an effective way to improve the city traffic operationefficiency as well as reduce environment pollution.Firstly, based on analyzing and summarizing the domestic and foreign publicbicycle’s application situation and the existing problems in the development of publicbicycles, points out the reasonable schedule mechanism and scientific and reasonablelocation is a necessary condition to improve public bicycle’s implementation effect.Secondly, based on the analysis of characters of public bike rental behavior, thispaper finds out the factors which have impact on the choice of public bike. Thenapplying random utility theory, establish the public bicycle demand forecast model.Use bicycles’ turnover rate and parking piles’ turnover rate to calculate bicycle andpile’s scale. Establish the Weighted Markov chain model to forecast the bicycle’sscheduling scale or increasing scale of the system.Finally, analysis the principles of public rental location’s scheme evaluationsystem and discus the system construction step and class each index. Establish aTOPSIS model from the planning department and the user’s perspective, and improvethe index weight’s determine, which combine the subjective weighting method (AHP)and objective weighting method (Maximizing Deviation Method) to determine theparameter weights’ effects, in order to objectively and comprehensively reflect theinfluence index’s importance and problem’s actual situation. In the last part of thepaper through an example to calculate and analysis the hole research process, thenverify the model’s feasibility.The work of the paper’s mainly reflected in:(1) Comprehensively analysis and introduce the domestic and foreign publicbicycle’s application situation;(2)Design a questionnaire and carry out a survey; (3)Attempt to apply the Weighted Markov chain model to forecast the bicycle’sscheduling scale or increasing scale of the system.（4）Improve the index weight’s determine of TOPSIS model.