Cinema,drone warfare and the framing of counter-terrorism

The study of the cinematic representation is extremely useful in framing of counter-terrorism policies, whether in the US or elsewhere. This paper examines cinema’s interest in drone warfare as well as the lives and personalities of drone pilots. It argues that drone warfare suffers a considerable image problem that has been brought out in several recent features and it is unlikely that any major cinematic myth of drone warfare will easily develop, certainly in comparison to myths concerning special forces and special operations.     

Optimal force mix in heterogeneous combat

This article presents models for determining the optimum number of Red weapons required to win a heterogeneous combat in which m(m> 1) types of Red weapons face a single type of Blue weapon under a newly defined termination policy. Red aims at either minimizing the total cost or maximizing the aggregated remaining force strength. Kuhn-Tucker and simulated annealing techniques are used for obtaining the optimal solution. The methodology is illustrated by analysing heterogeneous combat to determine (i) the feasibility of introducing new types of weapons and (ii) the number of weapons required to win if a specific type of weapon, say infantry, dominates. © 1995 John Wiley & Sons, Inc.     

Nature of renyi's entropy and associated divergence function

Nature of Renyi's entropy and associated divergence function is discussed in terms of concave (convex) and pseudoconcave (pseudoconvex) functions.     

A forward network simplex algorithm for solving multiperiod network flow problems

An optimization model which is frequently used to assist decision makers in the areas of resource scheduling, planning, and distribution is the minimum cost multiperiod network flow problem. This model describes network structure decision-making problems over time. Such problems arise in the areas of production/distribution systems, economic planning, communication systems, material handling systems, traffic systems, railway systems, building evacuation systems, energy systems, as well as in many others. Although existing network solution techniques are efficient, there are still limitations to the size of problems that can be solved. To date, only a few researchers have taken the multiperiod structure into consideration in devising efficient solution methods. Standard network codes are usually used because of their availability and perceived efficiency. In this paper we discuss the development, implementation, and computational testing of a new technique, the forward network simplex method, for solving linear, minimum cost, multiperiod network flow problems. The forward network simplex method is a forward algorithm which exploits the natural decomposition of multiperiod network problems by limiting its pivoting activity. A forward algorithm is an approach to solving dynamic problems by solving successively longer finite subproblems, terminating when a stopping rule can be invoked or a decision horizon found. Such procedures are available for a large number of special structure models. Here we describe the specialization of the forward simplex method of Aronson, Morton, and Thompson to solving multiperiod network network flow problems. Computational results indicate that both the solution time and pivot count are linear in the number of periods. For standard network optimization codes, which do not exploit the multiperiod structure, the pivot count is linear in the number of periods; however, the solution time is quadratic.     

When chaos reigns: responding to complex emergencies

This article discusses the impact of Complex Humanitarian Emergencies on the delivery of humanitarian aids. Complex emergencies were the results of long-term political and social disputes. Its impact brings about public health crises like epidemics, malnutrition, and even widespread desperation. In fact, there are four aspects of these crises which complicate public health programs: 1) emergencies are long and recurring; 2) access to the most vulnerable population is often restricted; 3) restructuring health systems in complex emergencies can be futile; and 4) complex emergencies often result in mass forced migration. What makes matters worse is the breakdown of health networks which collapse early in complex emergencies, leading to extensive losses of human health resources. Not only that, health facilities and transportation, infrastructure are often decimated in complex emergencies, and regional hospitals, district health posts, laboratories, and primary care outposts are similarly abandoned or destroyed. Moreover, because it is difficult to predict the course of these emergencies, ascertaining the optimal time to intervene and to invest in materials and facilities that could be lost to renewed fighting can be impossible. To solve this problem requires a coordinated effort. It should also focus on resources, early warning systems, preparedness measures, ongoing career training of relief workers, and prepositioning of relief supplies.     

A heuristic procedure for allocating tasks in fault-tolerant distributed computer systems

One way of achieving the increased levels of system reliability and availability demanded by critical computer-based control systems is through the use of fault-tolerant distributed computer systems. This article addresses the problem of allocating a set of m tasks among a set of n processors in a manner that will satisfy various task assignment, system capacity, and task scheduling constraints while balancing the workload across processors. We discuss problem background, problem formulation, and a known heuristic procedure for the problem. A new solution-improving heuristic procedure is introduced, and computational experience with the heuristics is presented. With only a modest increase in the amount of computational effort, the new procedure is demonstrated to improve dramatically solution quality as well as obtain near-optimal solutions to the test problems.     

On fractional programming and equivalence

Under fairly general conditions, a nonlinear fractional program, where the function to be maximized has the form f(x)/g(x), is shown to be equivalent to a nonlinear program not involving fractions. The latter program is not generally a convex program, but there is often a convex program equivalent to it, to which the known algorithms for convex programming may be applied. An application to duality of a fractional program is discussed.