The Scheduling Optimization Study Of Public Bicycle

Public bicycle is a convenient and green way of transportation,which can solve the "last mile" problem of bus travel.However,the public can't find a bicycle or to leave it at some stations sometimes.Scheduling bicycle reasonably can solve the problem.Scheduling optimization of public bicycle is to find a more reasonable scheduling model,to find a more efficient scheduling algorithm,to solve the problem of lending and returning the bicycle hardly.Efficient scheduling can save scheduling costs and improve public satisfaction with the public bicycles.It can promote the sustainable development of public bicycle system,alleviate traffic pollution and traffic congestion,promote the green travel of urban residents.Based on the analysis of the shortcomings of the current bicycle scheduling,the dynamic and static scheduling optimization of public bicycles are further studied in this paper.To improve the efficiency of scheduling,we established a mathematical model based on the mixed time window for the static scheduling of public bicycles,and established a two-stage mathematical model for the dynamic scheduling one.For the static scheduling,two algorithms are proposed in this paper: the hybrid Intelligent Water Drop algorithm and the adaptive hybrid Ant Colony algorithm.This is the first time introducing returning-service strategy to the Ant Colony algorithm,merging the improved Ant Colony algorithm with the Leapfrog mechanism to generate adaptive hybrid Ant Colony algorithm,and an Intelligent Water Drop algorithm is firstly merged with Simulated Annealing mechanism.For dynamic scheduling of public bicycles,we propose an improved hybrid Variable Neighborhood Search and Ant Colony algorithm.For the algorithm,the black ant mechanism and jumping exploration mechanism is firstly presented,a Neighborhood Search algorithm improved with element fitness and new neighborhood structure is presented,the ants are given a special perspective and the road traffic information.In addition,a dynamic scheduling strategy based on hybrid driven time slice is presented.The experimental results show that these new algorithms and strategies are better and more efficient.