Research On The Theory And Algorithm Of Large Scale Inventory And Warehouse Management

The following thesis presents the development and research of two projectsconducted by Department of Industrial Engineering aiming at the improvement ofinventory and warehouse efficiency of one internationally recognized heavy industrycompany. Based on the demand record, parts properties, receipt record, place orderrecord and supplier structureprovided by company, the document presents an algorithmto cope with stochastic lead time incurred in the supplier structure, with theconsideration of four different types of order patterns. After the determination ofinventory policy, an efficient placement heuristic is developed to assign different partsinto the warehousewith the additional input information of warehouse layout,transportation method and assignment constraint. The objective of storage assignmentheuristic is to reducing the picking and replenishment cost of the warehouse.The inventory optimization algorithm first considers the probability of shortage ofeach supplier in the cascade lineto form each line’s integrated lead time, then using theinformation of percentage of order processed in each line to form the integrated leadtime of the parallel system. Coupled with the information of demand, the algorithmcalculates the distribution of demand in one integrated lead time to determine theminimum re-order point satisfying the service level. Regarding the different orderpattern, the algorithm conducts an efficient two dimensional search of re-order pointand order quantity to find the optimal inventory policy which minimizes the long-runaverage inventory cost.The storage assignment heuristics gives higher assignment priority of groups ofparts which correspond to rare resource. Within each group, the heuristics fist assignsthose parts with smaller cube-per-order index (COI). A transportation method is chosenafterwards for each parts to minimize the picking and replenishment cost.The inventory algorithm shows an inventory cost reduction of each parts from5%to20%and a total inventory reduction of7%. Compared with the random assignmentadopted by the company, the small volume first assignment and high frequency firstassignment, the assignment heuristic based on COI index shows a constantoutperforming result.