Research On Optimization Algorithm Of Knapsack Problem In Express Logistics Distribution

The rapid development of the national economy and the innovation of modern science and technology led to the development of the logistics industry.As a result,the level and the overall size of the logistics in China have been greatly improved.With the increasing scale of logistics,the efficiency of logistics system is becoming more and more important.However,the logistics costs still account for a large proportion of GDP in our country.It indicates that although the scale of the logistics industry has been developed very impressive,the efficiency of logistics system is still relatively low in our country.In the whole logistics operation activities,the distribution process is closely related to the logistics enterprises and customers.So to improve the efficiency of distribution activities will help improve the operational efficiency of the logistics system.Every enterprise must consider the problem that how to reduce the unit cost during the transportation through designing a reasonable distribution program.In this case,this thesis researches the loading problem of vehicles in logistics(i.e.the knapsack problem in logistics).This thesis selects the particle swarm algorithm as the basic optimization algorithm after analyzing the algorithm that solve the knapsack problem.It is easy to implement and has a small number of parameters to be set in the algorithm.Moreover,it can balance between global search and local search at the same time.However,there is a problem that the basic particle swarm algorithm is easy to fall into the local optimum,and the convergence rate is slowed down at the later stage of optimization process.In this thesis,a suitable improved particle swarm algorithm is proposed to solve the problem of express logistics knapsack.This thesis mainly carried out the following work:1.In order to verify the effectiveness of the proposed algorithm,this thesis establishes a simulation model based on analyzing the internal operation flow of real logistics operation to simulate the whole real logistics operation activities.On this basis,it also establishes the express logistics knapsack model after analyzing the characteristics of express logistics knapsack problem.The virtual logistics simulation model system provides the simulation data and the platform for the verification of the algorithm.2.This thesis analyzes the characteristics of the basic particle swarm algorithm,and proposes the integrated optimization algorithm that fusing the particle swarm and the simulated annealing algorithm to optimize the knapsack problem of the express logistics.3.This thesis analyzes the reason that the vehicle loading rate is low on the path obtained by the pre-route optimization module.At first,an adjustment strategy is proposed to adjust the path.Then,the proposed algorithm is used to optimize the order on each path.Finally,it obtains the order distribution table of each path.This thesis implements the simulation experiment based in the data obtained from the model.And the experimental results show that the proposed algorithm can solve the problem of express logistics knapsack effectively.Also,the optimization effect of the proposed algorithm is better than other classical algorithms.