| In recent years,with the rapid development of our national economy,urban environmental problems have become increasingly prominent.In particular,air pollution problems led by the haze,have been sustained attention by the community.And the emission problem caused by automobile fuel consumption is one of the main reason of air pollution.The factors that affect vehicle fuel consumption mainly include load situation and speed.Therefore,in order to reduce the fuel consumption of urban logistics vehicles,we need to comprehensively consider the above points.Vehicle routing problem(VRP)is a classic problem of highway logistics distribution,in the current study,factors that considered in fuel consumption more concentrate on weight and distance,the study that comprehensively consider load,distance and speed is relatively few,this paper considers these three factors,to study the optimization of vehicle routing problem.In an urban environment,vehicle travel speeds during a day are not a constant value,traffic fluctuations seriously affect travel speeds,especially the congestion problem occurs in the rush hours,which significantly reduces travel speeds,resulting in a substantial increase of fuel consumption per 100 km.This phenomenon increases the complexity of the optimization of the a routing scheme to reduce fuel consumption.According to the characteristics of vehicle speed changes with time,this paper studies the model of vehicle routing problem with fuel consumption and its optimization method.Considering vehicle fuel consumption is determined by distance,weight and speed,this paper introduces the concept of time dependent,and establishes the model of time dependent vehicle routing problem aiming at minimize total fuel consumption.In this paper,the time dependent vehicle routing problem model includes vehicles departure time from the depot as decision variables.In addition,a two-stage solving algorithm for the problem is designed.In the first stage of the algorithm,the problem is solved by ant colony algorithm in the case of a given fixed departure time.In the second stage,one-dimensional search method is adopted to optimize the departure time of the solution,which yielded in the first stage.The result of calculation example shows that the ant colony algorithm can effectively reduce the fuel consumption in urban logistics distribution.At the same time,after the second stage,the optimal scheme is better than that of the first stage,and further reduces fuel consumption. |
