Research On Optimization Of Car-sharing Scheduling Based On Mixed Reward Mechanism

With the improvement of the overall living standard of residents,the public transport system has been unable to meet the increasingly diversified and personalized travel needs of residents.More and more families buy private cars for transportation,and even one family has more than two private cars.The resulting traffic congestion,environmental pollution and other phenomena are increasingly serious.Therefore,car sharing service emerges at the historic moment and gradually expands its market under the background of sharing economy,becoming one of the important travel choices for residents.As an emerging time-sharing rental service,car sharing has the advantages of improving vehicle utilization rate,alleviating traffic congestion,reducing harmful gas emissions,etc.,and its one-way stop-like operation mode also provides users with more convenient car service.The development of new things is often accompanied by various problems.Due to the unbalanced demand of users in time and space,the supply and demand of car sharing is unbalanced,which affects the utilization rate of car sharing and users’ sense of experience.Therefore,how to solve the uneven distribution of car sharing and plan the resulting vehicle scheduling has become one of the main challenges faced by enterprise management.In view of the imbalance between supply and demand of such vehicles,enterprises usually choose to dispatch professional dispatchers to dispatch vehicles.However,this approach not only has high dispatch cost,but also has poor flexibility,which will lead to the decrease of enterprise income and poor user experience.In the long run,it is very unfavorable to the future operation of the enterprise.Therefore,it is of great significance to study how to dispatch car sharing more efficiently and at a lower cost.Based on the above background,this paper studies the scheduling problem of car sharing.First of all,this paper reviews the relevant studies of many domestic and foreign scholars on car sharing.Since there are few literatures on the use of incentive mechanism to encourage users to participate in car sharing scheduling,other studies on car sharing optimization are also referred to.Secondly,based on certain preconditions and assumptions,using order selection strategy and mixed reward mechanism,a mixed integer programming model for sharing car scheduling optimization with profit maximization as the main goal is constructed.Considering the complexity of the calculation,an improved artificial jellyfish search optimizer is used to solve the model.After considering the advantages and disadvantages of the standard artificial jellyfish search optimizer,a chaotic initialization method based on Tent mapping is introduced to optimize the initial solution in this paper,and a new jellyfish individual updating method is designed to further optimize the diversity of the jellyfish population.Considering the discrete property of the model,a special encoding and decoding method is designed in this paper.In order to verify the effectiveness of the model and the performance of the improved artificial jellyfish search optimizer,this paper uses small,medium and large scale examples for testing.On the one hand,the mixed reward mechanism is compared with the two single reward mechanisms,which verifies that the mixed reward mechanism can improve the corporate revenue better.On the other hand,the improved artificial jellyfish search optimizer is compared with genetic algorithm,particle swarm optimization algorithm,simulated annealing algorithm and standard artificial jellyfish search optimizer.The final result proves that the improved artificial jellyfish search optimizer has stronger advantages than the other four algorithms.