Design And Implementation Of Intelligent Warehousing Collaborative Optimization Algorithms

With the popularization of the concept of intellectualization,industrial intellectualization has also embarked on the road of development under the call of the state.Whether it is a logistics enterprise or a production and processing enterprise,it is inevitable to use warehouse as a transit storage place for logistics.The concept of intellectualization plus warehouse emerged as the times require,that is,intellectualized warehouse.Intelligent warehousing has been from the beginning of theoretical research to the development stage of practical application.As a result,the research in this field has great research value and significance.Intelligent warehousing is divided into two parts: goods storage and goods transportation.At this stage,most of the optimization algorithms are carried out for these two parts.At present,there are many related studies on the optimization of shelf or space and path planning,and most of them have achieved excellent research results.However,the traditional research on intelligent warehouse optimization is basically independent.The research on shelf optimization focuses only on the optimal results of shelf placement,while the research on path planning focuses only on the efficiency of algorithm execution and optimization results.In essence,there is a certain degree of coupling between the two,and in some scenarios,the coupling between them is very high.Therefore,shelf optimization and path planning should not be calculated separately when intelligent warehouse optimization is carried out.They should be combined to participate in an optimization system.At present,there is little research on the collaborative optimization of shelf and path planning.This paper proposes a framework of collaborative optimization of shelf path based on the idea of collaborative optimization,combining and analyzing practical problems and needs.The main achievements of this paper are as follows:(1)This paper presents a mathematical model of coordinated optimization of shelf space through coupling analysis of the relationships among various parts of the intelligent warehousing link.The difference between the model and the traditional intelligent warehouse optimization algorithm is that the path planning and shelf optimization are grouped into a whole and the relationship between them is expressed by mathematical formulas.(2)The solution algorithm of intelligent warehousing cooperative optimization algorithm is given,including the similarity solution algorithm of goods and the improved path planning algorithm.On the basis of the above two algorithms,the improved genetic algorithm is used to realize the coordinated optimization of shelf path.Experiments and comparison algorithms are designed to further analyze the characteristics of the intelligent warehouse cooperative optimization algorithm implemented in this paper.(3)Design and implement a complete intelligent warehouse optimization solution,from graphical testing tools to data analysis algorithms,the basic tool class has been completed.Map tools store various types of maps internally,and provide interfaces to the outside world,which makes it easy to use various types of map program calls.Data analysis algorithm is a separate module.After inputting data,it can output results.which can be used for other purposes.The significance of this work lies in that,drawing lessons from the idea of collaboration,by re-analyzing the coupling relationship among goods,shelves and path planning in intelligent warehousing,a collaborative optimization framework of intelligent warehousing based on coordinated optimization algorithm of shelf path is proposed theoretically,which helps to improve the efficiency of warehousing and reduce transportation costs.At the same time,a flexible tool software is developed,which can be applied to other scenarios or projects.