| Recently, logistics is playing more and more important role in social and economic development, but also caused serious energy and environment problems. Reasonable vehicle route planning is viewed as one of the most important solutions to reduce logistics enterprises’ operation costs as well as alleviate the energy and environmental problems. This paper takes vehicle routing problem considering minimizing fuel consumption as the research object considering time windows, vehicle loading constraints, the impacts of loading and speed on energy consumption factor. Integer programming models are established and the improved ant colony algorithm is established to solve it. The aim is to complete distribution with minimal energy consumption. The main research content of this paper is as follows:Firstly, vehicle routing problems will be classified according to different criteria, and the characteristics of the commonly used algorithms will be analyzed.Secondly, considering the limitation of vehicle dimension and maximum loads, the impact of speed and load on energy consumption factor, three dimensional packing model and integrated model for calculating the fuel consumption are established. Then, using three dimensional packing model as restriction and using fuel consumption minimization as the optimization goal, the model of three dimensional loading capacitated-time dependent vehicle routing problems with time window considering fuel consumption is built.Then, aim at the above models, the ant colony algorithm is improved as follows:1) Considering the road network condition around customers and the cargo demand characteristics of customers, this paper proposes vehicles can stop at the alternative stop point which is at the other side of the road temporarily, to reduce the possible roundabout transport which is caused by vehicles only stopping at the road side where the customer is located;2) Using simulated annealing algorithm to solve the three-dimensional packing model, goods loading can meet the vehicle carrying capacity limit, do not overlap each other and meet last in first out (LIFO) rule;3) On the basis of fuel consumption ant pheromone concentration can be updated and the purpose of optimizing distribution scheme as well as reducing fuel consumption will be achieved;4) Based on the preliminary optimization results, considering the effect of speed and load on fuel consumption factor, by adjusting the departure time of distribution vehicles from the distribution center and the customers, the aim of reducing fuel consumption will be achieved using the dynamic traffic data.At last, using the real road network and dynamic traffic data of Beijing,6distribution instances with different customers are constructed and be solved using the above mathematical model and ant colony algorithm. The calculation results show that, compared with traditional methods, the optimization method proposed in this paper can make the fuel consumption during distribution reduce25.52%at most. |
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