Optimizing counter-terror operations: Should one fight fire with “fire” or “water”?

This paper deals dynamically with the question of how recruitment to terror organizations is influenced by counter-terror operations. This is done within an optimal control model, where the key state is the (relative) number of terrorists and the key controls are two types of counter-terror tactics, one (“water”) that does not and one (“fire”) that does provoke recruitment of new terrorists. The model is nonlinear and does not admit analytical solutions, but an efficient numerical implementation of Pontryagin's minimum principle allows for solution with base case parameters and considerable sensitivity analysis. Generally, this model yields two different steady states, one where the terror organization is nearly eradicated and one with a high number of terrorists. Whereas water strategies are used at almost any time, it can be optimal not to use fire strategies if the number of terrorists is below a certain threshold.     

Optimizing Investments in Security Countermeasures: A Practical Tool for Fixed Budgets

As a software engineer or client, how much of your budget should you spend on software security mitigation for the applications and networks on which you depend? The authors introduce a novel way to optimize a combination of security countermeasures under fixed resources. Software engineers and their customers continuously face a complex and frustrating decision: given a fixed budget, which combination of vulnerability mitigation actions produces optimal system security? In a world without budgetary or temporal constraints, engineers could invest in whatever tools or training they deemed necessary to safeguard applications and networks. Or they could spend arbitrary amounts of time and money patching existing code and take painstaking precaution in writing new software to ensure its security. Of course, the economic reality is that software engineers are pushed to get their product to market as fast as possible, and security is often a distant priority in the face of budgetary constraints. However, fixing any remaining security vulnerabilities postproduction can be both costly and wasteful. In this article, we describe a novel methodology for quantitatively optimizing the blend of architectural and policy recommendations that engineers can apply to their products to maximize security under a fixed budget. The results of our optimization are sometimes surprising and even counterintuitive: bigger budgets don't always produce greater security, and the optimal combination of corrective actions changes nonlinearly with increasing expenditures. These findings suggest that some form of formal decision support could augment traditional methods.     

Modelling the spread of hepatitis C via commercial tattoo parlours: implications for public health interventions

Hepatitis C (HCV) is a serious infection caused by a blood-borne virus. It is a contagious disease spreading via a variety of transmission mechanisms including contaminated tattoo equipment. Effectively regulating commercial tattoo parlours can greatly reduce this risk. This paper models the cost-effectiveness and optimal timing of such interventions, and parameterises the model with data for Vienna, Austria. This dynamic model of the contagious spread of HCV via tattooing and other mechanisms accounts for secondary infections and shows that regulating tattoo parlours as done in Vienna, Austria in 2003, is a cost-saving intervention.     

Brand image and brand dilution in the fashion industry

We develop a dynamic optimal control model of a fashion designer's challenge of maintaining brand image in the face of short-term profit opportunities through expanded sales that risk brand dilution in the longer-run. The key state variable is the brand's reputation, and the key decision is sales volume. Depending on the brand's capacity to command higher prices, one of two regimes is observed. If the price markups relative to production costs are modest, then the optimal solution may simply be to exploit whatever value can be derived from the brand in the short-run and retire the brand when that capacity is fully diluted. However, if the price markups are more substantial, then an existing brand should be preserved. It may even be worth incurring short-term losses while increasing the brand's reputation, even if starting a new brand name from scratch is not optimal.     

Long term implications of drug policy shifts: Anticipating and non-anticipating consumers

We consider a semi-rational addiction model in which the user has perfect foresight over all things within the user’s control, but not necessarily with respect to exogenous parameter shocks, e.g., those stemming from changes in national policy. We show that addictive substances are more likely to have state-dependent solution trajectories, and that in turn can create path dependence at the macro-policy level; in particular, legalization may be an irreversible experiment. Also, in this model, shifting from a nuanced policy that differentiates between high and low intensity users, to a tougher one where the government makes life hard for every user reduces initiation considerably. However, it also may have perverse effects. In particular, we show that making the policy tougher in this way could drive some people from a “happy” stable saddle point equilibrium with moderate consumption into increasing rather than reducing their consumption and addiction stock. So implementing zero tolerance policies may increase rather than reduce aggregate drug use, depending on the population’s distribution of parameter values and initial consumption stocks. Further, we consider the impact of announcing a policy change.     

Operations Research and public policy for Africa: harnessing the revolution in management science instruction

Operations Research (OR) has made major contributions in the developed world to public policy domains that are of great relevance to Africa. Inasmuch as OR has failed to live up to its potential for addressing such issues in Africa, a principal barrier may have been distance between OR analysts and decision makers. However, the revolution in management science instruction and potential to train end‐user modelers has democratized OR. This makes training for policy makers and managers in the public and non‐profit sectors in Africa both feasible and highly beneficial. Existing management science courses for public and non‐profit leaders, such as those taught at Carnegie Mellon's Heinz School, could be adapted to fit the needs of educators and policy makers in Africa and disseminated via a “train the trainers” approach. A plan is sketched whereby 800,000 end‐user modelers might be trained in Africa (one for every 1000 people) at an annual cost of about $5 million/year. Such budgets are well within the range of investments in human capital formation currently being made in Africa.