Study On Terminal Logistics Distribution Path Planning Considering Traffic Condition Constraints

With the rapid development of social economy and urbanization,people’s travel demand is generally increasing.However,the traffic conditions update slowly,which makes the urban traffic in China present the characteristics of infrastructure construction can not keep up with the rapid growth of traffic demand.In addition,the overall number of vehicles in China has increased year after year,which makes the traffic inconvenient,which has a great challenge to the logistics industry.Because the distribution cost accounts for a large proportion in logistics activities,logistics companies have to pay attention to the impact of traffic conditions on distribution activities if they want to effectively reduce the distribution cost and improve the distribution efficiency.In this paper,considering the traffic constraints,we establish a terminal distribution path model with traffic constraints,and the goal is to minimize the distribution cost.First of all,this paper analyzes different traffic restrictions and summarizes the actual impact of various situations on the distribution path model.Aiming at the forbidden traffic restrictions such as no passing,no turning and no two-way driving,a distribution path model represented by a special structure diagram-p-graph is established.The model takes advantage of the p-graph to effectively control the process information between nodes,and can well control whether different road sections are forbidden in the road network model.Secondly,the solution methods of the model are analyzed,and the solution time difference between the two algorithms is compared.By using p-graph studio modeling software,it is concluded that ABB algorithm is more efficient.For the distribution path model under congestion constraints,this paper studies the degree of congestion,obtains the evaluation method of congestion factor,and configures the congestion factor combined with travel time as congestion cost,which is added into the total distribution cost.Secondly,the characteristics of common heuristic algorithms are analyzed,and the defects of the selected ant colony algorithm are improved to solve the model.Finally,an actual regional scene is used to verify the practical significance of the proposed model and algorithm.There are 23 figures,13 tables and 87 references in this paper.