Research On Some Logistics Management Problems Based On Operations Research Methods

On the basis of relevant operations research optimization methods, the elements of logistics inventory costs are analyzed systematically. The logistics costs are used as the main clue. Two relevant improved economic order quantity models in enterprise logistics management are solved:time-varying partial backlogging EOQ model and soft time window EOQ model. A novel clustering algorithm is proposed and applied to the multi-item replenishment processing. This new algorithm has two distinguished features:non-binary hierarchical tree and the feature of overlapping clustering. The non-binary hierarchical tree is much smaller than the binary-trees constructed by most traditional algorithms and, therefore, it clearly highlights meaningful clusters which significantly reduce further manual efforts for cluster selections, so it provide minimal cost for multi facility location problem. The feature of overlapping clustering provides a better replenishment strategy for some single item that shares inventory patterns with more than one cluster. A simulation example for comparison illustrates the effectiveness of the proposed algorithm. Analytic Hierarchy Process is used to evaluate the performance of inventory management.