Parking Spots Selection for Shared Bicycle on Campus The xe2x80x9cshared bicyclexe2x80x9d has found a balance when facing the case xe2x80x9cdriving too close, taxis too expensive and walking too farxe2x80x9d, which helps to solve the last mile problem of people on daily life. The shared bicycle industry is developing rapidly, as the use of shared bicycles is more flexible and convenient than public bicycles. On the university campus, bicycles are a means of transportation for almost every student. Shared bicycle brings great convenience to the life of students and staff in universities, but it is followed by parking confusion and serious problems affecting campus order. Taking a certain campus of a wellknown university as an example, this paper establishes a multiobjective planning model, and uses the conversion method with LINGO solution to obtain the location plan of the shared bicycle parking point of the campus, which helps improve the campus sequence as well as the satisfaction of the shared bicycle users.

Balancing public bicycle sharing system using inventory critical levels in queuing network Abstract   Public Bicycle Sharing System has recently been developed and installed in many cities as a workable and popular transportation system. There are still some noticeable challenges associated with the operation of the system, like responding to all renting requests and all demands of vacant docks for returning bikes. Balancing the inventory of stations is necessary to minimize the rejected demands of bikes and the empty lockers. Here, critical levels are defined to control requests of different routes in which a demand of a specified destination is accepted if the inventory of the original station is higher than the routexe2x80x99s critical level. The capacity of stations and the fleet size are determined in addition to the different critical levels considering a constraint for the fleet size of the system. After developing the model using the Jackson network, a genetic algorithm is developed to obtain the proper amounts of variables for balancing the inventory of the system as much as possible. Finally, different examples are worked through to evaluate the applicability of the proposed method.