Probabilistic solution and bounds for serial inventory systems with discounted and average costs

We consider the infinite horizon serial inventory system with both average cost and discounted cost criteria. The optimal echelon base‐stock levels are obtained in terms of only probability distributions of leadtime demands. This analysis yields a novel approach for developing bounds and heuristics for optimal inventory control polices. In addition to deriving the known bounds in literature, we develop several new upper bounds for both average cost and discounted cost models. Numerical studies show that the bounds and heuristic are very close to optimal.© 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Untruthful probabilistic demand forecasts in vendor‐managed revenue‐sharing contracts: Coordinating the chain

Vendor‐managed revenue‐sharing arrangements are common in the newspaper and other industries. Under such arrangements, the supplier decides on the level of inventory while the retailer effectively operates under consignment, sharing the sales revenue with his supplier. We consider the case where the supplier is unable to predict demand, and must base her decisions on the retailer‐supplied probabilistic forecast for demand. We show that the retailer's best choice of a distribution to report to his supplier will not be the true demand distribution, but instead will be a degenerate distribution that surprisingly induces the supplier to provide the system‐optimal inventory quantity. (To maintain credibility, the retailer's reports of daily sales must then be consistent with his supplied forecast.) This result is robust under nonlinear production costs and nonlinear revenue‐sharing. However, if the retailer does not know the supplier's production cost, the forecast “improves” and could even be truthful. That, however, causes the supplier's order quantity to be suboptimal for the overall system. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Production to order and off‐line inspection when the production process is partially observable

This study combines inspection and lot‐sizing decisions. The issue is whether to INSPECT another unit or PRODUCE a new lot. A unit produced is either conforming or defective. Demand need to be satisfied in full, by conforming units only. The production process may switch from a “good” state to a “bad” state, at constant rate. The proportion of conforming units in the good state is higher than in the bad state. The true state is unobservable and can only be inferred from the quality of units inspected. We thus update, after each inspection, the probability that the unit, next candidate for inspection, was produced while the production process was in the good state. That “good‐state‐probability” is the basis for our decision to INSPECT or PRODUCE. We prove that the optimal policy has a simple form: INSPECT only if the good‐state‐probability exceeds a control limit. We provide a methodology to calculate the optimal lot size and the expected costs associated with INSPECT and PRODUCE. Surprisingly, we find that the control limit, as a function of the demand (and other problem parameters) is not necessarily monotone. Also, counter to intuition, it is possible that the optimal action is PRODUCE, after revealing a conforming unit. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Kurtosis correction method for X̄ and R control charts for long‐tailed symmetrical distributions

This paper proposes a kurtosis correction (KC) method for constructing the X? and R control charts for symmetrical long‐tailed (leptokurtic) distributions. The control charts are similar to the Shewhart control charts and are very easy to use. The control limits are derived based on the degree of kurtosis estimated from the actual (subgroup) data. It is assumed that the underlying quality characteristic is symmetrically distributed and no other distributional and/or parameter assumptions are made. The control chart constants are tabulated and the performance of these charts is compared with that of the Shewhart control charts. For the case of the logistic distribution, the exact control limits are derived and are compared with the KC method and the Shewhart method. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Subspace dynamic‐simplex linear interpolation search for mixed‐integer black‐box optimization problems

Design and management of complex systems with both integer and continuous decision variables can be guided using mixed‐integer optimization models and analysis. We propose a new mixed‐integer black‐box optimization (MIBO) method, subspace dynamic‐simplex linear interpolation search (SD‐SLIS), for decision making problems in which system performance can only be evaluated with a computer black‐box model. Through a sequence of gradient‐type local searches in subspaces of solution space, SD‐SLIS is particularly efficient for such MIBO problems with scaling issues. We discuss the convergence conditions and properties of SD‐SLIS algorithms for a class of MIBO problems. Under mild conditions, SD‐SLIS is proved to converge to a stationary solution asymptotically. We apply SD‐SLIS to six example problems including two MIBO problems associated with petroleum field development projects. The algorithm performance of SD‐SLIS is compared with that of a state‐of‐the‐art direct‐search method, NOMAD, and that of a full space simplex interpolation search, Full‐SLIS. The numerical results suggest that SD‐SLIS solves the example problems efficiently and outperforms the compared methods for most of the example cases. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 305–322, 2017     

Alleviating time inconsistent behaviors via a competition scheme

Under quasi‐hyperbolic discounting, the valuation of a payoff falls relatively rapidly for earlier delay periods, but then falls more slowly for longer delay periods. When the salespersons with quasi‐hyperbolic discounting consider the product sale problem, they would exert less effort than their early plan, thus resulting in losses of future profit. We propose a winner‐takes‐all competition to alleviate the above time inconsistent behaviors of the salespersons, and allow the company to maximize its revenue by choosing an optimal bonus. To evaluate the effects of the competition scheme, we define the group time inconsistency degree of the salespersons, which measures the consequence of time inconsistent behaviors, and two welfare measures, the group welfare of the salespersons and the company revenue. We show that the competition always improves the group welfare and the company revenue as long as the company chooses to run the competition in the first place. However, the effect on group time inconsistency degree is mixed. When the optimal bonus is moderate (extreme high), the competition motivates (over‐motivates) the salesperson to work hard, thus alleviates (worsens) the time inconsistent behaviors. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 357–372, 2017     

Probabilistic resource pooling games

We study a setting with a single type of resource and with several players, each associated with a single resource (of this type). Unavailability of these resources comes unexpectedly and with player‐specific costs. Players can cooperate by reallocating the available resources to the ones that need the resources most and let those who suffer the least absorb all the costs. We address the cost savings allocation problem with concepts of cooperative game theory. In particular, we formulate a probabilistic resource pooling game and study them on various properties. We show that these games are not necessarily convex, do have non‐empty cores, and are totally balanced. The latter two are shown via an interesting relationship with Böhm‐Bawerk horse market games. Next, we present an intuitive class of allocation rules for which the resulting allocations are core members and study an allocation rule within this class of allocation rules with an appealing fairness property. Finally, we show that our results can be applied to a spare parts pooling situation.     

基于效用函数的随伴支援炮兵弹药选择模型

随着火炮武器系统的发展,火炮所配属的弹药类型越来越多,针对不同目标选择合适的弹药以达到最佳作战效能具有重要意义。首先,按照"最大化对敌火力效果、最小化附带损伤,最小化费用"的原则,分析了随伴支援炮兵弹药选择模型要考虑的决策指标,包括毁伤比、压制比、非敌伤亡率、安全距离、费用。建立了决策指标的效用函数,在此基础上建立了整体的决策指标,对决策指标的权重系数进行了分析探讨。最后用实例证明该方法是一种有效综合各类因素的弹药选择方法,能够很好地解决弹药选择问题。     

一种定标缺失情况下的高光谱目标识别方法

高光谱遥感图像识别在民用和军事领域有着广泛的应用。在缺乏定标信息、缺乏同步观测大气光学参数情况下,对高光谱图像进行地物识别尚没有系统有效的方法,制约了其在定量遥感方向的应用。对此提出了一种利用粒子群算法优化6S模型参数基础上的高光谱遥感数据校正方法,并将其应用于定标缺失情况下的目标识别中。实验表明:在对遥感图像利用少许先验信息选择参数进行校正后,分类准确率为76.25%。而利用粒子群算法优化参数的6S校正后,分类准确率提高到91.58%,目标识别准确率得到了有效提高。     

美国陆军数据战略目标及实施

为深入研究美陆军数据战略目标及实施策略,为我军数据战略研究提供借鉴,文章对美陆军2016年发布的最新《陆军数据战略》进行分析,指出其目标是实现数据的可视化、可获取、可信任、可理解和互操作,并对美陆军数据战略的具体实施策略进行了剖析,指出美国陆军数据战略推动的是美军军事作战理论转型,从"网络为中心"转变为以"数据为中心"作战理念,其核心意图在于以数据优势实现指挥决策优势。