Research On Optimization Of Kunming Subway Spare Parts Inventory Control

This treatise starts from the experience of the spare parts management in the subway industry,investigates the spare parts management and inventory status of the Kunming subway,studies the spare parts inventory classification based on the multi-criteria spare parts inventory ABC classification model,applies the YAAHP classification software to obtain the classification results,and sorts the inventory order points and orders.The calculation formula and safety stock model are studied.By analyzing the internal connections,between the warehouses of the Kunming subway,and taking the minimum total inventory cost as the optimization goal,an inventory control model was constructed,and the model was solved using genetic algorithms.At the same time,Sheffield MATLAB genetic algorithm toolbox was used for programming calculation.On this basis,the exponential smoothing method and BP neural network forecasting method are used to forecast spare parts demand,and the forecasting methods and forecasting results are analyzed and compared.The treatise studies the performance evaluation of Kunming subway spare parts inventory control,applies ANP network analytic hierarchy process,establishes a Kunming subway spare parts inventory control performance assessment network model,invites experts to score inventory control performance indicators,and uses SUPER DECISION software to calculate weighted supermatrix and indicators.Using fuzzy evaluation method to get performance evaluation results through fuzzy operation.Finally,the treatise puts forward suggestions for the optimization of spare parts inventory management.