French intervention in Mali: strategic alliances,long-term regional presence?

The March 2012 coup in Mali opened the door to expanded territorial occupation in northern Mali by Tuareg separatists and subsequently armed Islamist extremists. French forces intervened at the behest of the interim government in Mali. This article examines how various actors frame the conflict to their advantage. While the Malian government and France are allies, the position of various Tuareg actors shift over time as they strategize and weigh the value of allegiance with the French. Local extremist organizations are labeled as terrorists and are targeted as enemies. This article argues that the conflict has been decontextualized and framed within the ‘war on terror’. France’s decision to intervene and to expand their regional military presence, rather than exit, is legitimized by the framing of their intervention as integral to counterterrorism efforts.     

Optimal resource allocation and redistribution strategy in military conflicts with Lanchester square law attrition

We address the problem of optimal decision‐making in conflicts based on Lanchester square law attrition model where a defending force needs to be partitioned optimally, and allocated to two different attacking forces of differing strengths and capabilities. We consider a resource allocation scheme called the Time Zero Allocation with Redistribution (TZAR) strategy, where allocation is followed by redistribution of defending forces, on the occurrence of certain decisive events. Unlike previous work on Lanchester attrition model based tactical decision‐making, which propose time sequential tactics through an optimal control approach, the present article focuses on obtaining simpler resource allocation tactics based on a static optimization framework, and demonstrates that the results obtained are similar to those obtained by the more complex dynamic optimal control solution. Complete solution for this strategy is obtained for optimal partitioning of resources of the defending forces. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

On the application and extension of system signatures in engineering reliability

Following a review of the basic ideas in structural reliability, including signature‐based representation and preservation theorems for systems whose components have independent and identically distributed (i.i.d.) lifetimes, extensions that apply to the comparison of coherent systems of different sizes, and stochastic mixtures of them, are obtained. It is then shown that these results may be extended to vectors of exchangeable random lifetimes. In particular, for arbitrary systems of sizes m < n with exchangeable component lifetimes, it is shown that the distribution of an m‐component system's lifetime can be written as a mixture of the distributions of k‐out‐of‐n systems. When the system has n components, the vector of coefficients in this mixture representation is precisely the signature of the system defined in Samaniego, IEEE Trans Reliabil R–34 (1985) 69–72. These mixture representations are then used to obtain new stochastic ordering properties for coherent or mixed systems of different sizes. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

An approximate dynamic programing approach to the development of heuristics for the scheduling of impatient jobs in a clearing system

A single server is faced with a collection of jobs of varying duration and urgency. Each job has a random lifetime during which it is available for nonpreemptive service. Should a job's lifetime expire before its service begins then it is lost from the system unserved. The goal is to schedule the jobs for service to maximize the expected number served to completion. Two heuristics have been proposed in the literature. One (labeled π^S) operates a static priority among the job classes and works well in a “no premature job loss” limit, whereas the second (π^M) is a myopic heuristic which works well when lifetimes are short. Both can exhibit poor performance for problems at some distance from the regimes for which they were designed. We develop a robustly good heuristic by an approximative approach to the application of a policy improvement step to the asymptotically optimal heuristic π^S, in which we use a fluid model to obtain an approximation for the value function of π^S. The performance of the proposed heuristic is investigated in an extensive numerical study. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010     

Modeling and analysis of uncertain time‐critical tasking problems

This paper describes modeling and operational analysis of a generic asymmetric service‐system situation in which (a) Red agents, potentially threatening, but in another but important interpretation, are isolated friendlies, such as downed pilots, that require assistance and “arrive” according to some partially known and potentially changing pattern in time and space; and (b) Reds have effectively limited unknown deadlines or times of availability for Blue service, i.e., detection, classification, and attack in a military setting or emergency assistance in others. We discuss various service options by Blue service agents and devise several approximations allowing one to compute efficiently those proportions of tasks of different classes that are successfully served or, more generally, if different rewards are associated with different classes of tasks, the percentage of the possible reward gained. We suggest heuristic policies for a Blue server to select the next task to perform and to decide how much time to allocate to that service. We discuss this for a number of specific examples. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006.     

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     

Optimal replacement of continuously degrading systems in partially observed environments

Motivated by wind energy applications, we consider the problem of optimally replacing a stochastically degrading component that resides and operates in a partially observable environment. The component's rate of degradation is modulated by the stochastic environment process, and the component fails when it is accumulated degradation first reaches a fixed threshold. Assuming periodic inspection of the component, the objective is to minimize the long‐run average cost per unit time of performing preventive and reactive replacements for two distinct cases. The first case examines instantaneous replacements and fixed costs, while the second considers time‐consuming replacements and revenue losses accrued during periods of unavailability. Formulated and solved are mixed state space, partially observable Markov decision process models, both of which reveal the optimality of environment‐dependent threshold policies with respect to the component's cumulative degradation level. Additionally, it is shown that for each degradation value, a threshold policy with respect to the environment belief state is optimal if the environment alternates between two states. The threshold policies are illustrated by way of numerical examples using both synthetic and real wind turbine data. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 395–415, 2015     

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     

Bioprotection of facilities

The anthrax attacks of 2001 energized research directed toward reducing health consequences from airborne contaminants by augmenting current heating ventilation and air-conditioning (HVAC) systems. Even during peacetime, interest will continue in improving HVAC components to reduce biocontaminants associated with sick building syndrome. Current HVAC design uses numerical simulation methods of ordinary differential equations to predict approximate performance. The authors show that state-space Laplace Transform calculations actually solve the underlying differential equations and yield algebraic expressions that provide new insight. To sharpen the arguments in favor of this methodology, attention is restricted to improving existing HVAC systems to increase protection from an external release of hazardous particulates. By nearly eliminating the need for dynamical simulation, the resulting methods can be applied to far more complex HVAC designs with little additional computational effort. The new methods reduce the time required for computation by three orders of magnitude. These algebraic methods also can be extended to disparate technical problems including internal particulate release, gas masks, and designing new protective buildings.     

Efficient algorithms for flexible job shop scheduling with parallel machines

Job shop scheduling with a bank of machines in parallel is important from both theoretical and practical points of view. Herein we focus on the scheduling problem of minimizing the makespan in a flexible two-center job shop. The first center consists of one machine and the second has k parallel machines. An easy-to-perform approximate algorithm for minimizing the makespan with one-unit-time operations in the first center and k-unit-time operations in the second center is proposed. The algorithm has the absolute worst-case error bound of k − 1 , and thus for k = 1 it is optimal. Importantly, it runs in linear time and its error bound is independent of the number of jobs to be processed. Moreover, the algorithm can be modified to give an optimal schedule for k = 2 .