Research On Optimization Of Initial Aisle Distribution And Inbound Planning In High Density Agile Delivery System

Nowadays logistics has developed into a pillar industry of the national economy.As a key part of logistic processes,warehousing plays an important role in the circulation of goods and the storage systems,With the continuous expansion of the scale of automobile enterprises,the logistics centers of the areas where automobile industries gather raise higher demands of scale and efficiency on the storage systems.Therefore,the research group has proposed the High Density Agile Delivery System which bases on the powered through shelves and gantry lifting shuttles.This paper studies the aisle distribution and inbound plan optimization problems of the High Density Agile Delivery System,which has important practical.This paper has analyzed the characteristics of the system's aisle distribution problem in detail,and according to the actual operation process of the system,established the balanced outbound aisle distribution model.Based on the established model,the MATLAB Genetic Algorithm has been designed.The outbound information of a logistics center has been taken as an example.And under different weight combinations,the simulation schemes of the aisle distributions have been obtained.Aiming at the long searching time and slow convergence rate of the Genetic Algorithm for the balanced outbound aisle distribution model,a Simulated Annealing Genetic Algorithm has been designed based on the original algorithm.And the simulation results have been compared with the original algorithm,which has proved the effectiveness and better searching ability of the Simulated Annealing Genetic Algorithm in this paper.The results also have proved that the Simulated Annealing Genetic Algorithm has also accelerated the convergence process.This paper has put forward the optimization target of the regular outbound aisle distribution and established the optimization model.The MATLAB Genetic Algorithm has been used to simulate the aisle distribution problem with different outbound information.The optimization results have been compared in detail and proved that the designed algorithm can achieve the expected optimization target,meet the requirements of the actual operation of the system and verify the validity and practicability of the designed algorithm.The model of the inbound plan optimization has been established.Taking the information of a distribution center as an example,according to the principle that the inbound operation can only be advanced,the genetic algorithm has been used to adjust the inbound plan.Then the optimization results have been obtained.By comparing the optimization results with the original inbound plan,the excellent performance of the optimized inbound plan has been verified.