Automatic Warehouse Optimization Of Emotional Bacteria Foraging Algorithm Based On Non-uniform Elimination Diffusion Probability

With the use of information technology to promote industrial transformation of industry 4.0 and the coming of the era,the manufacturing industry is facing a huge competitiveness.As a link with a large proportion of manufacturing cost investment,warehousing is an inevitable trend to realize the automatic management of warehousing operations.As the main carrier of warehousing automation,automated three-dimensional warehouse is facing the challenges of throughput,customer satisfaction,production and distribution progress.The optimization of automated three-dimensional warehouse also reflects the theory and the practical application value of industry.In this paper,the BIW automatic access system of an automobile manufacturing enterprise is taken as the research object,and the integrated optimization of location allocation and picking is carried out.Considering that automated warehouse is a discrete system,its optimization problem belongs to NP hard problem.At the same time,due to the limitation of the efficiency and scale of the traditional precise algorithm,it is difficult to obtain the optimal solution in a small time cost.In view of this,this paper uses the theory of improved intelligent optimization algorithm to optimize the automated warehouse.The main contents of this paper are as follows:(1)In view of the problem of large running time cost faced by the enterprise’s automated three-dimensional warehouse,the optimization model of execution time of two commands including storage and retrieval based on horizontal and vertical cumulative distribution function is constructed,the expected value of the function is regarded as the mathematical optimization model to maximize the operation efficiency of the media,in addition,the problems such as unbalanced workload of stackers,low stability of shelf,andgreat influence on product quality during the execution of in and out warehouse tasks are considered,and the related mathematical optimization model and constraints are constructed.(2)An emotional bacteria foraging algorithm based on nonuniform elimination diffusion probability distribution is proposed.Firstly,in the chemotaxis step,a search mechanism based on Gaussian distribution is proposed,which can construct different Gaussian functions in horizontal and vertical directions according to different targets,and use this function to track and predict the target position,so as to promote the information exchange between individuals and improve the tracking accuracy of the algorithm.Secondly,in order to ensure the diversity of the optimized population,the strategy of population diversity and optimal selection was implemented.Finally,in order to avoid the degradation of solution quality caused by the constant probability of individual bacteria in the process of elimination diffusion,linear and non-linear were used In order to save the time cost of the algorithm,the random value of dynamic factor is introduced,which is used to limit the bacterial individuals in the undefined search space.(3)The algorithm proposed in this paper is used to solve the integrated optimization model,and the results are compared with those of the original bacterial foraging algorithm,immune bacterial foraging algorithm and social learning adaptive bacterial foraging algorithm,and the effectiveness and superiority of the algorithm proposed in this paper are verified by simulation.