Research On Partition Scheduling Model Of Public Bicycle System

The development of the city is gradually expanding with the increasing of economy and population.Some problems become increasingly serious,such as the traffic,environmental pollution.The public bicycle system was developed in global cities because of the concept of green travel.The system provides a transportation which is efficient,environment friendly and sustainable.It also makes the residents more diversified way to travel.A city has built nearly 3000 stations,dropping nearly 70000 bicycles.Hundreds of visits daily amount borrow the car every day.Predictably,the system will continue to develop and promote usage amount of public bicycle.However,there are many problems in the public bicycle system.With the increasing of recognition and demand,the public bicycle system lacks a scientific and systematic mode to complete the task of scheduling.When there is no cycle or the cycle is too more to store,the existing scheduling mode assign the scheduling car to patrol.This scheduling model is not only inefficient,but also has a high burst and randomness.In addition,there is a problem in the current scheduling region division.The division of the region rely on the judgment on the land type and the subjective experience.Each dispatching exchanges between the scheduling area are frequent,and the path of each dispatching plan also exists a certain deviation.In this paper,partition and regional vehicle scheduling route have carried on the related research work.Actually,there are two kinds of relationships between each site,the distance and lease-return relationship.In this paper,they were combined to evaluate the similar degree between points.A new type of partition scheduling model was established to calculate the degree of connectivity between scheduling area.In order to minimize cost of transportation and maximize satisfaction,the penalty function was established based on time window constraint mechanism path planning of scheduling model.Finally,this paper obtained some data to put forward two models for the experiment.