Study On Logistics Distribution Vehicle Routing Problem Considering Energy Saving And Emission Reduction

With the increasing development of modern logistics industry,the demand for logistics distribution is more and more urgent.The customer's demands are increasing and trend to multi-variety and small-batch.How to make the planning of vehicle routing to meet customer satisfaction of mass distribution,as well as reduce fuel consumption and emission by a large extent,has become a research focus of logistics.This paper proposes a two phases optimization method on the basis of the vehicle routing problem with time windows and multi-vehicles.The proposed model aims to meet the needs of customers,and reduce energy consumption and carbon emission.The first phase of the optimization method provides a fuzzy hierarchial clustering method for customer grouping;The second phase formulates the optimization group-based VRP model and designs a useful algorithm with the targets of energy conservation and emission reduction.The main research contents and conclusions of this paper are as follows:(1)Based on the work of predecessors,this paper expounds the theoretical and practical vehicle routing problem for the domestic and international systematically.It also analyzes and summarizes the characteristics of the correlational models and algorithms.To sovle the problem,this paper puts forward the comprehensive discharge model to calculate the energy consumption and carbon emission.(2)By analyzing the main factors that can affect customer satisfaction,we point out seven factors which will affect the customer satisfaction,such as incorporating location analysis,service quality,service time,external similarity factor et al.To manage the qualitative and quantitative indicators,we propose two methods of data processing to get the attribute value.And on this basis,we establish the fuzzy similar matrix which is used to the fuzzy hierarchial clustering algorithm.To manage this complex problem we propose a reasonable customer grouping method in front of the decision-making of vehicle routing.Through analyzing the examples,it is shown that the customer group method will greatly enhance the efficiency of solving the optimization model.And the variance of service quality in the same group is much smaller than ungrouped cases,which indicates the customer grouping method can effectively improve the service quality of vehicle distribution.(3)On the basis of analyzing the relevant factors that affect vehicle energy consumption and carbon emission,we apply the comprehensive discharge model to calculate the energy consumption and carbon emission of vehicles.A generic time penalty cost function is propsed basing on demand of the customer service time.The group-based vehicle routing optimization models are proposed according to consider the constant speed and time varying speed respectively.A significant feature of the proposed model is that it targets to minimize the totlal costs including energy cost,carbon emission cost,time cost and fixed cost.The genetic algorithm are used to solve the model.Computational tests of MATLAB shows the model considering energy saving and emission reduction,reduces 6.5%carbon emissions and 8.9%total costs compared to the short circuit optimization model.The computational tests verify the effectiveness of the proposed optimization model and algorithm.