Estimating negative binomial demand for retail inventory management with unobservable lost sales

The importance of effective inventory management has greatly increased for many major retailers because of more intense competition. Retail inventory management methods often use assumptions and demand distributions that were developed for application areas other than retailing. For example, it is often assumed that unmet demand is backordered and that demand is Poisson or normally distributed. In retailing, unmet demand is often lost and unobserved. Using sales data from a major retailing chain, our analysis found that the negative binomial fit significantly better than the Poisson or the normal distribution. A parameter estimation methodology that compensates for unobserved lost sales is developed for the negative binomial distribution. The method's effectiveness is demonstrated by comparing parameter estimates from the complete data set to estimates obtained by artificially truncating the data to simulate lost sales. © 1996 John Wiley & Sons, Inc.     

Optimal base stock policies and truck capacity in a two-echelon system

With the recent trend toward just-in-time deliveries and reduction of inventories, many firms are reexamining their inventory and logistics policies. Some firms have dramatically altered their inventory, production, and shipping policies with the goal of reducing costs and improving service. Part of this restructuring may involve a specific contract with a trucking company, or it may entail establishing in-house shipping capabilities. This restructuring, however, raises new questions regarding the choice of optimal trucking capacity, shipping frequency, and inventory levels. In this study, we examine a two-level distribution system composed of a warehouse and a retailer. We assume that demand at the retailer is random. Since the warehouse has no advance notice of the size of the retailer order, inventory must be held there as well as at the retailer. We examine inventory policies at both the warehouse and the retailer, and we explicitly consider the trucking capacity, and the frequency of deliveries from the warehouse to the retailer. Both linear and concave fixed transportation costs are examined. We find the optimal base stock policies at both locations, the optimal in-house or contracted regular truck capacity, and the optimal review period (or, equivalently, delivery frequency). For the case of normally distributed demand we provide analytical results and numerical examples that yield insight into systems of this type. Some of our results are counterintuitive. For instance, we find some cases in which the optimal truck capacity decreases as the variability of demand increases. In other cases the truck capacity increases with variability of demand. © 1993 John Wiley & Sons, Inc.     

The Damoclean sword of offensive cyber: Policy uncertainty and collective insecurity

Cyberspace is a new domain of operation, with its own characteristics. Cyber weapons differ qualitatively from kinetic ones: They generate effects by non-kinetic means through information, technology, and networks. Their properties, opportunities, and constraints are comparable to the qualitative difference between conventional and nuclear weapons. New weapons and their target sets in a new domain raise a series of unresolved policy challenges at the domestic, bilateral, and international levels about deterrence, attribution, and response. They also introduce new risks: uncertainty about unintended consequences, expectations of efficacy, and uncertainty about both the target’s and the international community’s response. Cyber operations offer considerable benefits for states to achieve strategic objectives both covertly and overtly. However, without a strategic framework to contain and possibly deter their use, make state and non-state behavior more predictable in the absence of reciprocal norms, and limit their impact, an environment where states face persistent attacks that nonetheless fall below the threshold of armed conflict presents a policy dilemma that reinforces collective insecurity.     

Moving the techno-science gap in Security Force Assistance

This paper looks at the impact of military technology diffusion on military assistance operations (MAO), in the United States known as Security Force Assistance or SFA. The discussion looks conceptually at the role of technological change and how it interacts with martial cultures in military assistant operations. I argue that growing trends in science and technology suggest potential conflicts between culture and technology. Relying on a culture-technology model drawn from anthropology, the paper contends that new technologies will present increasing challenges for the emerging MAO landscape. The paper will illustrate that the techno-science gap will continue to grow as innovations such as robotics, sensors, and networks continue to develop. Finally, the paper will look at ways to overcome this conflict between culture and technology.     

Counterinsurgency as armed reform: The political history of the Malayan Emergency

Despite the emphasis in doctrine and academia that counterinsurgency is in its essence political, these operations are all too commonly discussed and approached as primarily military endeavors. Informed by the need to refocus counterinsurgency studies, this article revisits a foundational case of the canon – the Malayan Emergency – to discuss its political (i.e., not military) unfolding. The analysis distinguishes itself by emphasizing the diplomatic processes, negotiations, and deals that gave strategic meaning to the military operations underway. In so doing, the article also generates insight on the use of leverage and elite bargains in creating new political settlements and bringing insurgent conflicts to an end.     

Path optimization for the resource‐constrained searcher

We formulate and solve a discrete‐time path‐optimization problem where a single searcher, operating in a discretized three‐dimensional airspace, looks for a moving target in a finite set of cells. The searcher is constrained by maximum limits on the consumption of one or more resources such as time, fuel, and risk along any path. We develop a specialized branch‐and‐bound algorithm for this problem that uses several network reduction procedures as well as a new bounding technique based on Lagrangian relaxation and network expansion. The resulting algorithm outperforms a state‐of‐the‐art algorithm for solving time‐constrained problems and also is the first algorithm to solve multi‐constrained problems. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Optimal service rates of a service facility with perishable inventory items

In this paper we optimally control service rates for an inventory system of service facilities with perishable products. We consider a finite capacity system where arrivals are Poisson‐distributed, lifetime of items have exponential distribution, and replenishment is instantaneous. We determine the service rates to be employed at each instant of time so that the long‐run expected cost rate is minimized for fixed maximum inventory level and capacity. The problem is modelled as a semi‐Markov decision problem. We establish the existence of a stationary optimal policy and we solve it by employing linear programming. Several numerical examples which provide insight to the behavior of the system are presented. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 464–482, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10021     

Bicriteria product design optimization: An efficient solution procedure using AND/OR trees

Competitive imperatives are causing manufacturing firms to consider multiple criteria when designing products. However, current methods to deal with multiple criteria in product design are ad hoc in nature. In this paper we present a systematic procedure to efficiently solve bicriteria product design optimization problems. We first present a modeling framework, the AND/OR tree, which permits a simplified representation of product design optimization problems. We then show how product design optimization problems on AND/OR trees can be framed as network design problems on a special graph—a directed series‐parallel graph. We develop an enumerative solution algorithm for the bicriteria problem that requires as a subroutine the solution of the parametric shortest path problem. Although this parametric problem is hard on general graphs, we show that it is polynomially solvable on the series‐parallel graph. As a result we develop an efficient solution algorithm for the product design optimization problem that does not require the use of complex and expensive linear/integer programming solvers. As a byproduct of the solution algorithm, sensitivity analysis for product design optimization is also efficiently performed under this framework. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 574–592, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10031