Research On The Sorting Optimization Of "Storage And Sorting Integration" In Cigarette Logistic Distribution Center

With the rapid development of modern logistics industry,the role of logistics and distribution center is becoming more and more important.As a key part of the logistics distribution center,the work cost of order picking accounts more than 50% of the whole of distribution center.Optimized research on the sorting process can effectively reduce operating costs and improve distribution efficiency.In the tobacco industry,existing cigarette logistics distribution centers often use stocking caching systems as a transitional link between storage systems and sorting systems.However,with the growing of cigarette items and sales in recent years,the social demand has been moving toward more varieties,smaller batches and higher frequencies.The stocking caching area restricts the improvement of distribution efficiency,and there are many drawbacks,such as more equipment,complicated business processes and so on.In this background,cigarette logistics distribution center "storage and sorting integration" mode emerged as the times require.The mode starts with the logistics link through technology transformation to eliminate the stocking caching area,divide its functions into the storage and sorting links to form “the area of storage and sorting integration”,optimize the business processes,and improve distribution center sorting efficiency and storage capacity as a whole.This thesis conducts a comparative analysis of the warehouse layout and sorting process of cigarette distribution centers before and after the implementation of the "storage and sorting integration" mode in an enterprise,summarizes the model's theoretical knowledge.These studies provide theoretical support and guidance for enterprises to implement this model in the future.This thesis makes a intensive research of the order picking and the replenishment tactics under this mode,and establishes a corresponding model to solve the problem of unbalanced sorting tasks and difficult stacker crane scheduling problems in this model.First,respectively usingfuzzy c-means algorithm and adaptive genetic-fuzzy mean clustering algorithm to solve the sorting clustering model based on task equilibrium.The simulation results of the data obtained by MATLAB verify that the two algorithms are effective.The comparative analysis shows that adaptive genetic-fuzzy mean clustering algorithm has more advantages in algorithm stability and iterative efficiency.Then,the adaptive genetic-fuzzy mean clustering algorithm is applied to solve the order-picking optimization model.The order picking batches that obtained by the algorithm can reduce the number of times the Class B cigarettes are handled by the stacker by an average of 5 times.The optimization ratio is 18.5%.In this thesis,through the two clustering processes,distribution center effectively achieve averaging task on the sorting line,optimize the process of stackers outbound and inbound,and improve the delivery efficiency.