Heterogeneous Vehicle Assignment And Routing For Optimizing Pharmaceuticals Delivery

In recent years,due to the rapid development of the national economy,people's concept of drug consumption has undergone tremendous changes,and the concern for health has been continuously improved.At the same time,the arrival of population aging and the increase in the prevalence of chronic diseases and many other factors have promoted the level of medical consumption in China to gradually improve.The development prospects of the pharmaceutical circulation industry are very impressive.However,since 2017,the State Council has formulated and vigorously promoted the “two invoice system” policy for drugs.This policy has a fatal impact on pharmaceutical enterprises,making the pharmaceutical logistics market competition extremely fierce,forcing pharmaceutical enterprises to strengthen the construction of logistics distribution network system,enhance the terminal distribution capacity,control the cost of distribution,and improve delivery efficiency and service quality.Because the distribution cost accounts for a higher proportion of the total logistics cost,and the distribution routing arrangement will directly affect the timeliness of distribution,which will affect the customer service satisfaction.Therefore,the distribution routing optimization problem is crucial for the distribution cost control and efficiency improvement.Based on the above background,this paper focuses on the optimization of vehicle scheduling and distribution routing optimization in the city's drug distribution.First,the characteristics of the drug and its distribution status are analyzed.Because of the characteristics of pharmaceutical products with short life cycle,small size,light weight,and the fact that logistics companies begin to use different types of vehicles for deliveries which differ with respect to load capacity,fixed cost and variable cost,the contradiction between the assignment of vehicle and the constraints of loading and distribution time become more prominent.Based on this,research content is further determined as the multi-type vehicle assignment and distribution path integration optimization problem with fixed fleet size under the constraints of distribution time and carrying capacity.The problem is formulated as an integer programming model and the objective of the problem is defined as minimizing the sum of travel cost,which contains the fixed cost and variable cost of vehicle.Then,a hybrid particle swarm optimization algorithm is designed to solve the problem,which fuse the crossover and mutation operation in genetic algorithm,and 2-opt local search strategy and design a principle based the cost network and Dijkstra's algorithm for vehicle scheduling,which can balance the contradiction between the distribution time limit and the high loading rate.Finally,numerical experiments are carried out based on two instances to verify the reliability of the algorithm and the practical effectiveness of the proposed model and algorithm respectively.In the numerical experiment of the standard instance,the near optimal solution can be obtained in a short time.Considering only the variable cost,the optimal solution can be obtained,which is consistent with the best known solution in the literature,and the deviation between the optimal solution and the best known solution given in the literature is only 0.4% when considering both the fixed cost and the variable cost.The experimental results based on different vehicle scheduling principles verify the superiority of the principle proposed in this paper;In the numerical experiment of the actual instance,the intelligence transportation scheme based on the proposed hybrid algorithm is compared with the distribution scheme based on the rule of thumb,the results show that the proposed model and algorithm can effectively reduce the distribution cost by 35.1% and increase the vehicle loading rate by 54.7%,indicating the practical validity of the proposed model and algorithm.