In order to solve the 'last mile' problem, bicycle sharing systems are rapidly developing in many cities. Meanwhile during the practical operation phase, the quantities of bikes and vacant lockers can't meet the fluctuating demand. The reason is complex; besides the disequilibrium of spatial and temporal distribution in demanding of bicycles and lockers, the scales of lockers and the quantities of bicycles at the initial time are two crucial factors affecting the operational condition of the sharing systems. This paper presents the modeling aiming to achieve the latest repositioning time during the morning peak time, combining the practical operational condition to optimize the scales of lockers and the quantities of cycles at the initial time. Improved genetic algorithm is used to achieve the model and obtain a high quality solution to this frequent everyday instance.
展开▼
