Research communication security in the 90s: A view from the UK

This paper develops a methodology for measuring the capital value of military assets in monetary terms. We distinguish between two military capital measures. One measure, called the value of military capital (services) summarizes the value of military defense assets during a particular year. A comparison of the capital‐services value of U.S. and Soviet tactical combat aircraft is provided for the period 1970–1984.

One feature of the capital‐services measure that makes it particularly interesting is that its size can be compared with such military expenditures as operating and support. While these latter expenditures reflect the readiness of a defense establishment, the relevant capital‐services measure reflects force structure and modernization.

A second measure, called the value of military capital (wealth), summarizes the military benefits obtained from defense assets over the remainder of their service lives. This measure depreciates the capital as it ages, and is useful for comparing military wealth with other types of wealth in the economy. We provide this measure for the U.S. military capital stock for 1925–1984.     

Inventory financing under Risk-Adjusted-Return-On-Capital criterion

Risk-Adjusted-Return-On-Capital (RAROC) is a loan-pricing criterion under which a bank sets the loan term such that a certain rate of return is achieved on the regulatory capital required by the Basel regulation. Some banks calculate the amount of regulatory capital for each loan under the standardized approach (“standardized banks,” the regulatory capital is proportional to the loan amount), and others under the internal rating-based (IRB) approach (“IRB banks,” the regulatory capital is related to the Value-at-Risk of the loan). This article examines the impact of the RAROC criterion on the bank's loan-pricing decision and the retailer's inventory decision. We find that among the loan terms that satisfy the bank's RAROC criterion, the one that benefits the retailer the most requires the bank to specify an inventory advance rate in addition to the interest rate. Under this loan term, the retailer's inventory level is more sensitive to his asset level when facing an IRB bank compared to a standardized bank. An IRB (standardized) loan leads to higher profit and inventory level for retailers with high (low) asset. For retailers with medium asset, an IRB loan results in a higher retailer profit but a lower consumer welfare. Calibrated numerical study reveals that the benefit of choosing standardized banks (relative to IRB banks) can be as high as 30% for industries with severe capital constraints, volatile demands, and low profit margins, highlighting the importance for retailers to carefully choose the type of banks to borrow from. When the interest rate is capped by regulation, retailers borrowing from a standardized bank are more likely to be influenced by the interest rate cap than those borrowing from an IRB bank. Under strong empire-building incentives (the bank will offer loan terms to maximize the size of the loan), retailers with medium initial asset level shift their preference from IRB banks to standardized banks.     

Operations sequencing for a multi‐stage production inventory system

This article studies operations sequencing for a multi‐stage production inventory system with lead times under predictable (deterministic) yield losses and random demand. We consider various cases with either full or partial release of work‐in‐process inventories, for either pre‐operation or post‐operation cost structures, and under either the total discounted or average cost criteria. We derive necessary and sufficient criteria for the optimal sequence of operations in all cases. While the criteria differ in their specific forms, they all lead to the same principal: those operations with (1) lower yields, (2) lower processing costs, (3) longer lead times, and (4) lower inventory holding costs should be placed higher upstream in the system.Copyright © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 144–154, 2014     

Dynamic pricing in a dual‐market environment

This article is concerned with the determination of pricing strategies for a firm that in each period of a finite horizon receives replenishment quantities of a single product which it sells in two markets, for example, a long‐distance market and an on‐site market. The key difference between the two markets is that the long‐distance market provides for a one period delay in demand fulfillment. In contrast, on‐site orders must be filled immediately as the customer is at the physical on‐site location. We model the demands in consecutive periods as independent random variables and their distributions depend on the item's price in accordance with two general stochastic demand functions: additive or multiplicative. The firm uses a single pool of inventory to fulfill demands from both markets. We investigate properties of the structure of the dynamic pricing strategy that maximizes the total expected discounted profit over the finite time horizon, under fixed or controlled replenishment conditions. Further, we provide conditions under which one market may be the preferred outlet to sale over the other. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 531–549, 2015     

Optimal and asymptotically optimal policies for assemble‐to‐order n‐ and W‐systems

We consider two specially structured assemble‐to‐order (ATO) systems—the N‐ and W‐systems—under continuous review, stochastic demand, and nonidentical component replenishment leadtimes. Using a hybrid approach that combines sample‐path analysis, linear programming, and the tower property of conditional expectation, we characterize the optimal component replenishment policy and common‐component allocation rule, present comparative statics of the optimal policy parameters, and show that some commonly used heuristic policies can lead to significant optimality loss. The optimality results require certain symmetry in the cost parameters. In the absence of this symmetry, we show that, for systems with high demand volume, the asymptotically optimal policy has essentially the same structure; otherwise, the optimal policies have no clear structure. For these latter systems, we develop heuristic policies and show their effectiveness. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 62: 617–645, 2015     

军事虚拟仓库应急保障仿真分析

在分析应急物流研究成果基础上,探索应用虚拟仓库理论和仿真技术研究应急物流中的协同库存问题.为此,构建了军事虚拟仓库系统及其协同控制系统动力学仿真模型,并针对军民、军军仓库间的应急物流协同保障策略进行仿真分析,结果表明这种方法可以在应急状态下合理调度和管理各类仓库资源,改进应急物流条件下仓库保障能力.     

Economic ordering decisions with market choice flexibility

Standard approaches to classical inventory control problems treat satisfying a predefined demand level as a constraint. In many practical contexts, however, total demand is comprised of separate demands from different markets or customers. It is not always clear that constraining a producer to satisfy all markets is an optimal approach. Since the inventory‐related cost of an item depends on total demand volume, no clear method exists for determining a market's profitability a priori, based simply on per unit revenue and cost. Moreover, capacity constraints often limit a producer's ability to meet all demands. This paper presents models to address economic ordering decisions when a producer can choose whether to satisfy multiple markets. These models result in a set of nonlinear binary integer programming problems that, in the uncapacitated case, lend themselves to efficient solution due to their special structure. The capacitated versions can be cast as nonlinear knapsack problems, for which we propose a heuristic solution approach that is asymptotically optimal in the number of markets. The models generalize the classical EOQ and EPQ problems and lead to interesting optimization problems with intuitively appealing solution properties and interesting implications for inventory and pricing management. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

Capacity games for partially complementary products under multivariate random demands

In this study, we consider n firms, each of which produces and sells a different product. The n firms face a common demand stream which requests all their products as a complete set. In addition to the common demand stream, each firm also faces a dedicated demand stream which requires only its own product. The common and dedicated demands are uncertain and follow a general, joint, continuous distribution. Before the demands are realized, each firm needs to determine its capacity or production quantity to maximize its own expected profit. We formulate the problem as a noncooperative game. The sales price per unit for the common demand could be higher or lower than the unit price for the dedicated demand, which affects the firm's inventory rationing policy. Hence, the outcome of the game varies. All of the prices are first assumed to be exogenous. We characterize Nash equilibrium(s) of the game. At the end of the article, we also provide some results for the endogenous pricing. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 59: 146–159, 2012     

Coordinated pricing and inventory control problems with capacity constraints and fixed ordering cost

This article addresses a single‐item, finite‐horizon, periodic‐review coordinated decision model on pricing and inventory control with capacity constraints and fixed ordering cost. Demands in different periods are random and independent of each other, and their distributions depend on the price in the current period. Each period's stochastic demand function is the additive demand model. Pricing and ordering decisions are made at the beginning of each period, and all shortages are backlogged. The objective is to find an optimal policy that maximizes the total expected discounted profit. We show that the profit‐to‐go function is strongly CK‐concave, and the optimal policy has an (s,S,P) ‐like structure. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Integrated capacity,demand, and production planning with subcontracting and overtime options

Models for integrated production and demand planning decisions can serve to improve a producer's ability to effectively match demand requirements with production capabilities. In contexts with price‐sensitive demands, economies of scale in production, and multiple capacity options, such integrated planning problems can quickly become complex. To address these complexities, this paper provides profit‐maximizing production planning models for determining optimal demand and internal production capacity levels under price‐sensitive deterministic demands, with subcontracting and overtime options. The models determine a producer's optimal price, production, inventory, subcontracting, overtime, and internal capacity levels, while accounting for production economies of scale and capacity costs through concave cost functions. We use polyhedral properties and dynamic programming techniques to provide polynomial‐time solution approaches for obtaining an optimal solution for this class of problems when the internal capacity level is time‐invariant. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007