Research On Location Problem Of Distribution Center Based On Improved Cuckoo Search Algorithm

As an important node in logistics system,distribution center plays a vital role in the process of material circulation.Reasonable distribution center location can not only improve the efficiency of material distribution,improve customer satisfaction,but also reduce the distribution cost effectively,and enhance the core competitiveness of enterprises.Therefore,the study on the distribution center location problem has important theoretical value and practical significance.Intelligent algorithm realizes the problem optimization by simulating the law of natural system,its solution precision is obviously improved compared with the traditional optimization methods,and the computation amount is greatly reduced,which significantly saves the economic and time cost,and provides a more effective method to solve the complex combinatorial optimization problem in real life.Therefore,it has become a very important and effective method to use intelligent algorithm to solve the distribution center location problem.Cuckoo algorithm is an intelligent optimization algorithm to simulate cuckoo spawning to find parasitic nest bionic behavior,which has attracted the attention of scholars because of its advantages of simple structure,few control parameters,excellent search path and the strong global optimization ability.At present,it has been widely used in various fields,providing a favorable tool for solving complex practical problems.However,it also has some disadvantages such as low precision and easy to fall into local optimization in the later stage.Therefore,in order to explore an effective optimization method,this paper improves the cuckoo algorithm and applies it to the solution of distribution center location problem.Based on this,this article mainly does the following work:Firstly,the basic cuckoo algorithm is improved,and the Cuckoo Search Algorithm(DWCS)with nonlinear inertial weight logarithmic decrement and stochastic adjustment discovery probability is proposed in the view of the problems such as slow convergence speed,low precision and easy to fall into local optimization in the later stage of the cuckoo algorithm.The algorithm can coordinate the exploration and development ability of cuckoo algorithm,which is beneficial to the balance of global exploration and local development of the algorithm,accelerate the algorithm convergence speed and increase the population diversity.By testing 16 functions,the DWCS algorithm can converge to the global optimalsolution,greatly improve the optimization accuracy,significantly reduce the number of iterations,and effectively improve the convergence speed and robustness.Compared with the improved cuckoo algorithm and other evolutionary algorithm,the improved algorithm in this paper has a strong competitive power in solving the problem of continuous complex function optimization.Secondly,the DWCS algorithm is used to solve the location problem of continuous single distribution center based on the precise center of gravity method.The circulation results of the DWCS algorithm are verified by two examples of continuous single distribution center selection,and the performance optimization comparison is carried out with the basic cuckoo search algorithm(CS),the improved cuckoo algorithm(ICS)and the particle swarm optimization algorithm(PSO).Simulation results show that the DWCS algorithm converges faster,has higher solution quality and strong robustness when solving the first and second examples.Finally,the DWCS algorithm is used to solve the problem of discrete multi-distribution center location based on CFLP model.By example three and example four,the DWCS algorithm is verified to solve the operation effect of discrete multi-distribution center location,and the results are compared with those of other evolutionary algorithms.Simulation results show that the convergence speed of DWCS algorithm is faster and more stable in the solution of the third and forth examples.In summary,through four distribution center location examples,it is proved that the DWCS algorithm is feasible and effective in solving the location problem of distribution center,which provides a new solution for the location of logistics distribution center.