Optimization And Simulation Of Automatic Cache Location Allocation Based On Multi-Objective Optimization Algorithm

At present,due to the growing demand for fast-moving consumer goods(FMCG)in the market,the demand for FMCG has increased,leading to a shift in business work towards FMCG.Taking the logistics and warehousing industry as an example,the industry faces problems such as long picking paths,long time consumption,low efficiency of cargo allocation processes,low warehouse operation efficiency,and long shuttle transportation time.Therefore,this article proposes an optimization method for cargo allocation based on reality,taking the special fast-moving consumer product of special-shaped cigarettes as an example.Taking a tobacco logistics company in C city as an example,data on irregular cigarettes were collected and two methods were used to verify the reliability and effectiveness of optimizing the allocation of cargo spaces.The research content is as follows:(1)Research on multi-objective optimization algorithm based on improved NSGA-II.This article takes the relevant data collected from the field as an example input,uses classical genetic algorithm to reproduce the on-site cargo allocation scheme,and assigns algorithm improvement experiments to this allocation scheme.The improvement effect is somewhat improved compared to the current local allocation.However,considering the principles of balanced and balanced delivery of goods based on actual needs,we will shift from a single dimension to a multi-dimensional approach.In view of this,this article focuses on establishing a multi-objective mathematical model for cargo space allocation,and uses multi-objective optimization algorithms MOEA/D,NSGA-II,and improved NSGA-II to compare and solve the mathematical model,obtaining corresponding optimization allocation results.(2)Research on modeling and simulation experiments.To verify the reliability and effectiveness of the multi-objective cargo location optimization allocation results mentioned above,Flexsim simulation experiments were used to verify the situation at the application level of three dimensions.Using UG to construct the physical structure of C city logistics automation cache library;Use ANSYS to load the specified load on the force surface of the designated location for cargo allocation,and the simulation results show that the cargo allocation is reliable.It has high reference significance for improving the operational efficiency of irregular cigarettes in the cache system,thereby improving the sorting efficiency of the lower sorting line system,and the overall operational efficiency of the logistics system.After Flexsim validation,taking a small batch as an example,the total time from the entry and exit to sorting of shaped cigarettes before and after optimization was reduced by 1034.18 seconds.Taking mass production as an example,the overall efficiency of warehouse allocation has increased by 8.47%.After ANSYS verification,the maximum equivalent stress(von Mises)of the optimized automatic cache library is 37.63 Mpa,and the maximum equivalent elastic strain is 1.88 × 10-4mm/mm.The safety factor of any position on the overall shelf is calculated to meet the specified requirements.This validation analysis experiment was validated using Flexsim and ANSYS.More strongly indicates that the optimization of warehouse location allocation has been substantially improved.By establishing a customer-oriented cargo allocation mechanism,we aim to maximize enterprise efficiency while ensuring service levels.