Research On Location Model Of Bike Sharing Launch Points

Shared bicycle has become an important part of urban traffic system because of its convenient and fast advantages.However,shared bicycle is still a new product in our country.There are relatively few scholars who study the location of shared bicycle.Therefore,it is of great practical and theoretical significance to construct an effective and reasonable optimal location model of shared bicycle delivery point for the development of shared bicycle enterprises.According to the characteristics of users’ bicycle demand,a median cost optimization location model of shared bicycle system is constructed based on deterministic users’ bicycle demand.The minimal total cost of fixed cost,management cost,purchase cost,variable cost and user’s walking cost is solved,and the bicycle delivery volume,location and full load point of each input point are determined.Which users need to ride? Considering that the quantity of bicycle demand is unbalanced in time and space,the minimum of total cost is solved,and then the robustness is introduced to construct a median cost optimization location model of shared bicycle system based on uncertain users’ bicycle demand.The decision variables are still the amount of bicycle put in at each place,the location of the place where the bicycle is put in and how the bicycle demand is allocated.Using Java software,20 users’ cycling demand points and 8 alternative delivery points are generated randomly.Lingo optimization software is used to solve the cost optimization location model of shared bicycle system based on demand determination and demand uncertainty respectively.By adjusting the robustness level,service level and correlation coefficient,the following conclusions can be drawn:(1)Robustness level has a significant impact on the location of shared bicycle drop-in points.The bigger the robustness level is,the more points to put in shared bicycles,the larger the total number and scale to put in,the greater the total cost of the system;the smaller the robustness level is,the fewer points to put in shared bicycles,the smaller the total number and scale to put in,the smaller the total cost of the system.(2)Service level has a significant impact on the total cost of location of shared bicycle drop-in points,and the effect is different in different ranges.When the service level Se of the delivery point is low,the increase of cost is controlled within 20%.When the service level Se of the delivery point reaches a certain value,the cost of the system increases exponentially.(3)The total cost of locating shared bicycle drop-in points is highly sensitive to the uncertainty of users’ cycling needs.With the increasing uncertainty of users’ cycling demand,the total cost of the system is also increasing,and with the continuous growth of service level Se at the launch point,the sensitivity is gradually enhanced.(4)The sensitivity of the total cost of locating a shared bicycle drop-in point to each component of its cost varies.The total cost of the system is not sensitive to the fixed cost of the delivery point,the management cost of the delivery point and the user’s walking cost;it is sensitive to the purchase cost and variable cost of the bicycle,and the sensitivity increases with the increase of the robustness level.