The Research On Urban Vehicle Routing Optimization For Energy Saving And Emission Reductzhuanion

In recent years,problems like increasingly depleted fossil fuels and global warming have attracted close attention from governments.In order to solve these problems effectively,governments have put forward the important measure of greenhouse gas(mainly carbon dioxide)emission reduction to achieve sustainable development.For example,in December 2017,China held a conference on the carbon emissions trading system,which included more than 1700 enterprises for the first time to approve carbon emissions quotas and linked the energy-saving and emission-reduction directly to the enterprise cost.According to the report issued by the International Energy Agency,the CO2 emission from the logistics and transportation industry accounts for 25% of the total emissions in the world.Therefore,in order to reduce the carbon emission and finally reduce the enterprise cost effectively,it's of necessity to optimize the management of the enterprise logistics,which is the "third profit source" after material and human resources.However,in existing logistics enterprises,there are many problems that lead to a large increase in energy consumption and carbon emissions.For example,the extension of the enterprise delivery and customer waiting time caused by limitations like daytime peak trip and road restriction,and the phenomenon of empty and high no-load rate caused by single cycle scheduling.In order to solve these problems and finally reduce the enterprise distribution cost,this paper presents a new scene of night distribution and studies the optimization and application of urban vehicle routing problem oriented to energy saving and emission reduction in this scenario.The main contents include:Firstly,the basic operation and components of common vehicle routing problem are analyzed,and the problem description and basic mathematical models of the classic VRP,VRP with load constraint and VRP with time window are collated.Meanwhile,the problems and shortcomings of the existing urban vehicle routing optimization are summarized,and hence the urban path optimization problem for energy saving and emission reduction is put forward.Additionally,characteristics,key problems to be solved and the solution to the optimization problem are also pointed out.Secondly,the scientific calculation method is employed to calculate all the cost of the urban night LCVRPTW model,including the cost of carbon tax,the cost of the heavy oil consumption,the departure cost of the urban night multi-vehicles,the depreciation cost of vehicles and tires at night,the salary of night cargo drivers and the penalty cost of the time window.And consequently the urban night LCVRPTW model is established.Thirdly,the advantages and disadvantages of existing VRP algorithms are compared.According to the contrast results,the genetic algorithm with high robustness and better global search ability is selected to solve the proposed optimization model.Simultaneously,in light of the shortcomings of the existing genetic algorithm,it is improved in the following four links: coding and decoding of chromosomes,Sweep initialization population,crossover operator design and elite reservation algorithm for father participation.And finally an improved genetic algorithm(GA)operation flow is proposed.Finally,in an urban distribution route optimization project,the urban night LCVRPTW model is established combined with specific coordinate and demand data of the customer point,which is obtained by the previous investigation.Appropriate model and algorithm parameters are set up and then the improved genetic algorithm is used to solve the established model.Thus,the distribution route and the match with minimum comprehensive cost are obtained.