Location Allocation And Multi-person Job Picking Path Optimization In Warehouse Management System

With the development of computer technology and the advancement of enterprise informatization,the warehouse management systems of small and medium-sized enterprises are springing up in an endless stream,providing an effective platform for information collection,recording and management in the warehouse.With the increase of warehouse entry and exit tasks,location allocation and picking path optimization become the key to improve warehouse storage capacity and operation efficiency.The traditional bookkeeping warehouse management system can no longer meet the current warehousing and picking requirements.Therefore,the development of a warehouse management system with the function of automatically optimizing the allocation of goods and picking paths has important practical significance for the development of small and medium-sized enterprises.Genetic algorithm has inherent implicit parallelism and good global optimization ability.It runs fast and easily finds the optimal solution.It has good performance in solving the optimization model of goods location allocation and picking path.However,as the number of iterations increases,the search efficiency of the algorithm becomes lower and lower,and it is easy to fall into the local optimal solution.To solve the above problems,an improved genetic algorithm is proposed to solve the optimization model of location allocation and picking path.On this basis,a prototype system of warehouse location allocation and picking path optimization for small and medium-sized enterprises is designed and implemented.The main work of this dissertation is as follows:(1)A Multi-population Genetic Location Allocation Algorithm Based on Improved Selection Operator(IMGA-LA)is proposed to solve the problem of location allocation and optimization,and to meet the demand of storage management system for small and medium-sized enterprises.Considering the effects of cargo turnover rate,cargo correlation,shelf stability and the matching relationship between cargo and cargo location on warehouse storage capacity and operation efficiency,amulti-target optimization model of cargo location allocation is established.In the process of solving the model by genetic algorithm,the cumulative probability is used to improve the selection operator to ensure the good of the descendant population and improve the search efficiency of the algorithm;the genetic mechanism of multiple populations is used to increase the diversity of the population,so that the algorithm is not easy to fall into the local optimal solution.Comparing IMGA-LA algorithm with GA,IGA and PSO algorithm on specific data sets,the results show that the proposed algorithm has significantly improved in global search ability,convergence and stability,and in storage capacity and operation efficiency of warehouse,and there is also a significant improvement in the storage capacity and operational efficiency of the warehouse.(2)A Multi-population Genetic Order-picking Optimization Algorithm Based on Time Window Constraints(TWCMGA-OPO)is proposed to solve the problem of multi-user job-picking path optimization and meet the optimization requirements of warehouse management system for small and medium-sized enterprises.Considering the distribution of picking tasks,the conflict of picking paths and how to find the shortest picking paths caused by manual operation in warehouse of small and medium-sized enterprises,an optimization model of multi-user picking paths is established,which aims at the shortest length of picking paths.In the process of solving the model,the time window algorithm is used to analyze the path set,and the overlapping time window of the same section is adjusted to eliminate the path conflict.The experimental results on a specific data set show that the length of picking path obtained by this algorithm is reduced by 6.09%?4.45% and 6.72% compared with GA,IGA and PSO,respectively.At the same time,considering the parallelism of multi-user picking,the picking time can be reduced by multiple times.(3)Based on the requirement analysis of the warehouse management system of small and medium-sized enterprises and the above-mentioned location allocation and multi-user order-picking optimization algorithm,a warehouse management prototype system for small and medium-sized enterprises running on client and Android with the function of location allocation and order-picking optimization is designed andimplemented by using MySQL and SQLite database and Java language.The system test results show that the system meets the basic needs of warehouse management,and also meets the optimization requirements of location allocation and goods picking path.