供应链下的多级存货管理外文文献内容摘要:

houses, and they exist intransit, or ‘in the pipeline’, on each path linking these facilities. Manufacturers procure raw material from suppliers and process them into finished goods, sell the finished goods to distributors, and then to retail and/or customers. When an item moves through more than one stage before reaching the final customer, it forms a ‘multiechelon’ inventory system. The echelon stock of a stock point equals all stock at this stock point, plus intransit to or onhand at any of its downstream stock points, minus the backorders at its downstream stock points. The analysis of multiechelon inventory systems that pervades the business world has a long history. Multiechelon inventory systems are widely employed to distribute products to customers over extensive geographical areas. Given the importance of these systems, many researchers have studied their operating characteristics under a variety of conditions and assumptions. Since the development of the economic order quantity (EOQ) formula by Harris (1913), researchers and practitioners have been actively concerned with the analysis and modeling of inventory systems under different operating parameters and modeling assumptions .Research on multiechelon inventory models has gained importance over the last decade mainly because integrated control of SCs consisting of several processing and distribution stages has bee feasible through modern information technology. Clark and Scarf were the first to study the twoechelon inventory model. They proved the optimality of a basestock policy for the pureserial inventory system and developed an efficient deposing method to pute the optimal basestock ordering policy. Bessler and Veinott extended the Clark and Scarf model to include general arbores cent structures. The depotwarehouse problem described above was addressed by Eppen and Schrage who analyzed a model with a stockless central depot. They derived a closedform expression for the orderuptolevel under the equal fractile allocation assumption. Several authors have also considered this problem in various forms. Owing to the plexity and intractability of the multiechelon problem Hadley and Whitin remend the adoption of singlelocation, singleechelon models for the inventory systems. Sherbrooke considered an ordering policy of a twoechelon model for warehouse and retailer. It is assumed that stock outs at the retailers are pletely backlogged. Also, Sherbrooke constructed the METRIC (multiechelon technique for coverable item control) model, which identifies the stock levels that minimize the expected number of backorders at the lowerechelon subject to a bud get constraint. This model is the first multiechelon inventory model for managing the inventory of service parts. Thereafter, a large set of models which generally seek to identify optimal lot sizes and safety stocks in a multiechelon framework, were produced by many researchers. In addition to analytical models, simulation models have also been developed to capture the plex interaction of the multiechelon inventory problems. So far literature has devoted major attention to the forecasting of lumpy demand, and to the development of stock policies for multiechelon SCs Inv。
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