考虑地震冲击的自动化立体仓库货位分配方法

Allocation Method of Three-dimensional Warehouse Space Considering Seismic Shock

为降低地震冲击致使仓储中心货架坍塌的风险,提高货架的稳定性,本文以立体货架货位分配为研究对象,提出了一种考虑地震冲击的立体仓库货位分配方法。在分析地震下货架的受力基础上,建立了以货物出入库能耗、货架稳定性及频繁项货物就近存储的多目标货位分配模型,同时采用理想点法对目标函数进行变形,构造本文算法的适应度函数,同时结合模型的特点,从算法编码、步骤等设计了人工鱼群算法。最后,通过对比仿真实验分析了地震冲击、地震影响系数和不同算法对货位分配求解结果的影响,结果表明本文提出的方法能有效解决考虑地震冲击的货位分配问题。

Traditional research on the stability of shelves only takes the lowest overall center of gravity in the vertical direction of three-dimensional space as the optimization objective,and rarely considers the collapse of shelves caused by external forces such as sudden natural disasters.Under the impact of the earthquake,whether the warehouse center can withstand the test of the earthquake and operate normally,avoid huge property losses,and reduce the life safety risks for the staff,has become a matter of practical significance.Simultaneously,the shelves are not always in full load state in the daily production process,and the distribution of goods also directly affects the force and safety of the shelf structure.In order to reduce the risk of shelf collapse caused by earthquake and improve the stability of storage center shelves,this paper takes three-dimensional shelf space allocation as the research object,and puts forward a three-dimensional warehouse space allocation method considering earthquake impact.Firstly,this paper selects the energy consumption of goods in and out of storage,frequent items nearby storage and shelf stability considering earthquake shock as targets,constructs a multi-objective model,and uses the ideal point method to deform the objective function to obtain the fitness function of the proposed algorithm.Then,combining with the characteristics of the model,the coding and solving steps of the Artificial Fish Swarm Algorithm(AFSA)are rationalized,and the solving algorithm suitable for the problem in this paper is obtained.Then,taking the data collected from an e-commerce warehouse as an example,the simulation experiment is carried out:1)The FP-Tree algorithm is used to mine the sample order and obtain the frequent item set.2)The AFSA is used to solve the three sub-objectives,and three ideal points are obtained,and the fitness function of the proposed algorithm is constructed.3)The algorithm designed in this paper is used to obtain the optimized cargo space allocation results,and 1660 customer orders are randomly generated.The optimized cargo space allocation results are used to calculate the order picking distance,and the effectiveness of this algorithm to solve the problem is verified.Finally,multiple sets of comparison experiments are designed:1)In order to verify whether the cargo space allocation method considering earthquake shock is reasonable,AFSA is used to simulate and optimize the cargo space allocation model considering earthquake shock and not considering earthquake shock respectively.After 20 times of simulation,the average value is taken as the final optimization result,so as to ensure the stability and reliability of simulation experiment results.2)We change the horizontal seismic influence coefficient,and other variables of the model and algorithm remain unchanged.We use the AFSA to solve the corresponding total target value under different horizontal seismic influence coefficients,and analyze the influence of horizontal seismic influence coefficient on the solution results.3)In order to verify the superiority of artificial fish swarm algorithm in solving the problem in this paper,it is compared with genetic algorithm(GA)and particle swarm optimization algorithm(PSO).The results show that:1)In this paper,the space allocation method designed under the earthquake impact does not reduce the energy consumption of goods in and out of storage and the optimization effect of order picking efficiency,but improves the overall stability of shelves and enhances the ability of shelves to withstand the earthquake impact.2)The method in this paper is applicable to warehouse space optimization problems in different intensity areas,which can reduce energy consumption of warehouse goods in and out of storage and improve shelf stability.3)In solving the problem in this paper,the optimization effect of artificial fish swarm algorithm is better than that of genetic algorithm and particle swarm optimization algorithm.