Analysis of practical policies for a single link distribution system

In this paper we consider a transportation problem where several products have to be shipped from an origin to a destination by means of vehicles with given capacity. Each product is made available at the origin and consumed at the destination at the same constant rate. The time between consecutive shipments must be greater than a given minimum time. All demand needs to be satisfied on time and backlogging is not allowed. The problem is to decide when to make the shipments and how to load the vehicles with the objective of minimizing the long run average of the transportation and the inventory costs at the origin and at the destination over an infinite horizon. We consider two classes of practical shipping policies, the zero inventory ordering (ZIO) policies and the frequency‐based periodic shipping (FBPS) policies. We show that, in the worst‐case, the Best ZIO policy has a performance ratio of . A better performance guarantee of is shown for the best possible FBPS policy. The performance guarantees are tight. Finally, combining the Best ZIO and the Best FBPS policies, a policy that guarantees a performance is obtained. Computational results show that this policy gives an average percent optimality gap on all the tested instances of <1%. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Designing safety space in a supply chain to handle system‐wide disruptions

In some supply chains serious disruptions are system wide. This happens during periods of severe weather, as when storms cause shuttle tankers serving oil platforms in the North Sea to stop movements of crude oil, barges are frozen in the Mississippi, or all airplanes are grounded after a blizzard. Other notable instances of system‐wide disruption happened after the attack on the World Trade Center when all aircraft were grounded and the natural gas and crude‐oil pipelines were tangled by hurricanes in 2005. We model a situation where shutting down supply facilities is very difficult and expensive because of excessive inventory buildup from an inability to move out the production. We present a planning model that balances the cost of spare capacity versus shutting down production when planning for disruptions. The model uses an assignment model embedded in a simulation. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

An economic lot‐sizing problem with perishable inventory and economies of scale costs: Approximation solutions and worst case analysis

The costs of many economic activities such as production, purchasing, distribution, and inventory exhibit economies of scale under which the average unit cost decreases as the total volume of the activity increases. In this paper, we consider an economic lot‐sizing problem with general economies of scale cost functions. Our model is applicable to both nonperishable and perishable products. For perishable products, the deterioration rate and inventory carrying cost in each period depend on the age of the inventory. Realizing that the problem is NP‐hard, we analyze the effectiveness of easily implementable policies. We show that the cost of the best Consecutive‐Cover‐Ordering (CCO) policy, which can be found in polynomial time, is guaranteed to be no more than (4 + 5)/7 ≈ 1.52 times the optimal cost. In addition, if the ordering cost function does not change from period to period, the cost of the best CCO policy is no more than 1.5 times the optimal cost. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

教材印量决策模型研究

根据院校教材的需求特点及自印教材的费用发生特点,研究提出了３种适合于院校自印教材印量决策的随机库存模型．所提出的模型实用性强,对节省院校教材保障经费将起到直接的作用．     

备件库存限量分析及决策模型

分析了备件库存管理所对应的库存控制策略及其有关的因素,以费用为目标函数、不缺备件概率为约束条件,运用概率论及库存论原理建立了备件库存限量的决策摸型。     

Distribution free bounds for service constrained (Q,r) inventory systems

A classical and important problem in stochastic inventory theory is to determine the order quantity (Q) and the reorder level (r) to minimize inventory holding and backorder costs subject to a service constraint that the fill rate, i.e., the fraction of demand satisfied by inventory in stock, is at least equal to a desired value. This problem is often hard to solve because the fill rate constraint is not convex in (Q, r) unless additional assumptions are made about the distribution of demand during the lead‐time. As a consequence, there are no known algorithms, other than exhaustive search, that are available for solving this problem in its full generality. Our paper derives the first known bounds to the fill‐rate constrained (Q, r) inventory problem. We derive upper and lower bounds for the optimal values of the order quantity and the reorder level for this problem that are independent of the distribution of demand during the lead time and its variance. We show that the classical economic order quantity is a lower bound on the optimal ordering quantity. We present an efficient solution procedure that exploits these bounds and has a guaranteed bound on the error. When the Lagrangian of the fill rate constraint is convex or when the fill rate constraint does not exist, our bounds can be used to enhance the efficiency of existing algorithms. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 635–656, 2000     

Pareto-optimality in classical inventory problems

In this paper the inventory problem with backorders both deterministic and stochastic is studied using trade-off analysis in the context of vector optimization theory. The set of Pareto-optimal solutions is geometrically characterized in both the constrained and unconstrained cases. Moreover, a new way of utilizing Pareto-optimality concepts to handle classical inventory problems with backorders is derived. A new analysis of these models is done by means of a trade-off analysis. New solutions are shown, and an error bound for total inventory cost is provided. Other models such as multi-item or stochastic lead-time demand inventory problems are addressed and their Pareto-optimal solution sets are obtained. An example is included showing the additional applicability of this kind of analysis to handle parametric problems. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 83–98, 1998     

Warehouse sizing to minimize inventory and storage costs

This paper considers a warehouse sizing problem whose objective is to minimize the total cost of ordering, holding, and warehousing of inventory. Unlike typical economic lot sizing models, the warehousing cost structure examined here is not the simple unit rate type, but rather a more realistic step function of the warehouse space to be acquired. In the cases when only one type of stock‐keeping unit (SKU) is warehoused, or when multiple SKUs are warehoused, but, with separable inventory costs, closed form solutions are obtained for the optimal warehouse size. For the case of multi‐SKUs with joint inventory replenishment cost, a heuristic with a provable performance bound of 94% is provided. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 299–312, 2001     

基于自适应遗传算法的配送型多级库存优化研究

研究了由1个战役仓库、多个战术仓库组成的配送型系统的优化问题,建立了战术仓库使用经济订货批量策略和战役仓库采用4种不同订货策略时的模型,并采用自适应遗传算法实现了模型的求解,实例验证了模型及算法的有效性。     

Inventory transshipment game with limited supply: Trap or treat

Inventory transshipment is generally shown to be beneficial to retailers by matching their excess demand with surplus inventory. We investigate an inventory transshipment game with two newsvendor-type retailers under limited total supply and check whether the retailers are better off than the case without transshipment. We derive the ordering strategies for the retailers and show that unlike the unlimited supply case, a pure Nash equilibrium only exists under certain conditions. Furthermore, contrary to the conventional wisdom, we show that inventory transshipment may not always benefit both retailers. Although one of the retailers is guaranteed to be better off, the other could be worse off. The decision criteria are then provided for the retailers to determine if they will benefit from the exercise of inventory transshipment. Numerical study indicates that the carefully chosen transshipment prices play an important role in keeping inventory transshipment beneficial to both retailers. Subsequently, a coordinating mechanism is designed for the retailers to negotiate transshipment prices that maximize the total profit of the two retailers while keeping each of them in a beneficial position.