Research On Location Planning Of Sharing Bicycle Parking Sites Considering Uncertainties

In recent years,with the rapid development of the sharing economy and the popularization of technologies such as the Internet,the Internet of Things,and wireless communication networks,sharing bicycle have solved the problem of the ‘last mile’ of residents’ travel due to their non-pile and stop-and-go use.Accessibility blind zone of urban public transportation.However,due to the expanded development of sharing bicycle,the lagging industry management standards and the imperfect slow traffic service facilities system,it has brought many problems such as random parking and other problems,which has seriously affected the development of sharing bicycle and people’s normal lives.The facilities of sharing bicycle parking points belong to the system of slow traffic service facilities,and the perfect and reasonable slow traffic facilities can effectively solve the above problems.Bicycle sharing is still an emerging product.In the past,there was little research on the location of sharing bicycle parking spots,and more research on urban public bicycles.The qualitative or traditional random utility theory method was used in demand analysis,and the location planning model determined by parameters was used.In the case of changes in the external environment,the system goal is no longer optimal,resulting in unbalanced borrowing and demand,disorderly parking and parking ‘difficult to park’,‘difficult to borrow a car’ and other problems.Therefore,this paper studies the location planning of sharing bicycle parking spots,and the specific work is as follows:First,through mining and analyzing the sharing bicycle riding data set,the space-time travel demand characteristics of the sharing bicycle are obtained,and then the DBSCAN spatial clustering algorithm is used to cluster the sharing bicycle starting and parking coordinate points,and the demand for the sharing bicycle is large.The cluster point is used as the demand point,and the initial demand is obtained at the same time to complete the demand analysis.Then,comprehensively consider the minimum sum of the construction and operation costs of decision makers and the generalized travel costs of travellers,and construct a deterministic site planning model.On this basis,a robust optimization theory is introduced to incorporate demand and cost uncertainty into the site selection.Planning model,using ‘box uncertainty set’ and ‘ellipsoidal uncertainty set’ to characterize the change of uncertain parameters,introducing disturbance ratio and uncertainty level at the same time,constructing a sharing bicycle robust optimal location planning considering uncertainty factors model.Finally,the urban rail transit stations around which there is a strong demand for sharing bicycle are selected as case analysis objects.The model is verified by examples and solved using lingo.After considering the uncertain factors,the analysis box and the ellipsoidal uncertainty set are different.The impact of disturbance ratio and uncertainty level on site planning layout and total cost,as well as the changing relationship between service level and total cost,the case proves that the robust optimization model can enhance the stability and reliability of the system,which is more realistic In this situation,decision makers can choose different combinations of disturbance ratios and uncertainty levels according to their own risk preference and actual application situation,and trade off between robustness and total cost.