A Study On Two Inventory Models For Equipment Spare Parts

As our military reform unceasingly thorough, equipment spare parts management forequipment support system is becoming more and more important and received moreconcern. The efficiency of equipment spare parts management will directly affect the forceof the daily combat readiness, training and carry out diversified military tasks. Therefore,this thesis focuses how to combine the current research on the advanced theories, to furtherimprove the spare parts management awareness, to clear the management decision-makingtrain of thought, how to improve equipment spare parts management benefits scientificallyand effectively under limited costs.First of all, the characteristics of spare parts and principle of classification of spare partsare analyzed and the management characteristics of the equipment spare parts aresummarized. The current problems of equipment spare parts management are concluded andthe corresponding optimization strategy is put forward. Moreover, we also points out thatusing the quantitative analysis to improve the equipment spare parts management level is aneffective way. Secondly, the problem of an enterprise of initial spare parts quantity wasdiscussed under the reliability constraint, an algorithm using differential evolution algorithmis proposed based on the character of the model. Thirdly, the inventory strategies of anenterprise were analyzed, a multi-objective (Q, r) model is constructed under three criteriaof minimization of the annual expected total relevant cost, the annual expected frequency ofstock-out occasions, and the annual expected number of stock-outs quality. A hybridalgorithm is designed using GA and differential evolution algorithm to generatenon-dominated solutions. Then, an entropy theory-based technique for order preference bysimilarity to ideal solution is adopted to sort the non-dominated solutions to give usefuladvices for decision makers.