| Order picking is an important part of the process of distribution center. Its efficiencyhas an effect on the operations of distribution center. Therefore, the study of pickingmethods and strategies is meaningful. Conventional study on batch picking often aims tominimize the total travel distance or travel time. But book picking has its own features,those methods are not so match. Orders are grouped into batches based on association ruledata mining and0-1integer programming.In this thesis, solutions are put forward to improve the efficiency of the bookstoredistribution center with the combination of theory and practice. Firstly, the operationprocesses of bookstore distribution center are described and its characteristics are summedup. Then several evaluation indicators are chose to measure the operation efficiency.Secondly, the customers are classified using the EIQ analysis and suitable pickingstrategies of each portion are determined. Then batch order picking model is built withfinding the associations between orders by apriori algorithm and establishing0-1integerprogramming to maximize the support value between orders. Thirdly, this model is appliedinto HBWH Xinhua Bookstore Distribution centers. Analyzing its actual problems, somesolutions are proposed which is suitable for Xinhua Bookstore. In the process, investmentshould be made sure not to increase. Finally the effectiveness of the proposed solutionshave been verified. |
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