Analysis of decentralized multi‐product pull systems with lost sales

We study a pull‐type, flexible, multi‐product, and multi‐stage production/inventory system with decentralized two‐card kanban control policies. Each stage involves a processor and two buffers with finite target levels. Production stages, arranged in series, can process several product types one at a time. Transportation of semi‐finished parts from one stage to another is performed in fixed lot sizes. The exact analysis is mathematically intractable even for smaller systems. We present a robust approximation algorithm to model two‐card kanban systems with batch transfers under arbitrary complexity. The algorithm uses phase‐type modeling to find effective processing times and busy period analysis to identify delays among product types in resource contention. Our algorithm reduces the effort required for estimating performance measures by a considerable margin and resolves the state–space explosion problem of analytical approaches. Using this analytical tool, we present new findings for a better understanding of some tactical and operational issues. We show that flow of material in small procurement sizes smoothes flow of information within the system, but also necessitates more frequent shipments between stages, raising the risk of late delivery. Balancing the risk of information delays vis‐à‐vis shipment delays is critical for the success of two‐card kanban systems. Although product variety causes time wasted in setup operations, it also facilitates relatively short production cycles enabling processors to switch from one product type to another more rapidly. The latter point is crucial especially in high‐demand environments. Increasing production line size prevents quick response to customer demand, but it may improve system performance if the vendor lead‐time is long or subject to high variation. Finally, variability in transportation and processing times causes the most damage if it arises at stages closer to the customer. © 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     

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     

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。     

基于云模型和FAHP熵权的空地弹药效能评估

准确、科学地评估空地弹药的作战效能,对武器装备的设计、研制、试验、采购、作战使用及维护具有重要的意义。充分利用云模型可将定性指标的模糊性和随机性有效结合的特点,构建了空地弹药作战效能的综合云评估模型。针对现有确定指标权重的方法存在主观性较强的不足,提出一种基于模糊层次分析法(FAHP)熵权的权重确定方法,有效利用了主观信息和客观信息。实例分析表明该模型可准确、客观、有效地评估空地弹药的作战效能。     

航空弹药供应保障存在的问题及对策

在现代高技术信息化战争中,航空弹药地位和作用日渐突出。在分析了信息化条件下现代战争对航空弹药供应保障提出的新需求基础上,指出了航空弹药供应保障存在的不足,并从航空弹药的储备、管理和供应三个方面分别提出了相应的对策。研究表明,着眼应急作战的实际需要,搞好航空弹药供应保障,提高应急作战弹药供应保障能力,是摆在面前的一个现实而又紧迫的任务。     

远程制导火箭子母弹对机场跑道毁伤研究

对机场跑道毁伤封锁是远程制导武器的重要任务,其毁伤判断的依据是最小升降窗口存在与否。采用Monte-Carlo方法对远程制导火箭子母弹打击机场跑道的炸点分布进行仿真模拟,提出了一种改进的搜索飞机起降最小升降窗口算法,并用该算法计算分析了远程制导火箭子母弹相关战技术因素对机场跑道毁伤的影响程度。计算结果表明改进算法计算封锁概率的值相对于区域搜索算法更加精确,研究结果对远程制导火箭子母弹的作战运用及进一步优化设计具有参考与实用价值。     

基于规则的CGF实体行为建模技术

CGF行为建模的目的是使行为模型能更好地体现出人类行为特征,提高作战仿真系统的可信性和科学性。在介绍CGF、CGF行为建模概念的基础上,对当前几种主要的CGF行为建模方法进行了比较,并分析了CGF行为模型的一般结构。构建了基于规则的CGF行为模型,重点对基于规则CGF行为模型的决策推理方法进行了研究。采用产生式规则方法对决策知识进行了描述,定义了决策推理过程中的3个要素:态势、动作、决策推理,并对其决策推理过程进行了研究。     

基于模糊层次分析法的非致命弹药安全管理系统评价

针对非致命弹药安全管理评估方面的空白,采用模糊层次分析法（FAHP）,从宏观上对非致命弹药安全管理系统进行评价。通过分析影响非致命弹药安全管理水平的因素,建立系统综合评价指标。分别建立不同指标间的模糊一致判断矩阵,确定隶属函数、权重值,最后得出定量评判结果,确定非致命弹药安全管理系统等级,对非致命弹药安全管理提供理论依据。     

弹药保障决策模型的研究

从弹药保障的工作入手 ,论述了弹药消耗预计算法 ,提出了基于存储论的弹药补充决策模型。给出了战时弹药保障的 3种策略