Min/max bounds for dynamic network flows

This paper presents an algorithm for determining the upper and lower bounds for arc flows in a maximal dynamic flow solution. The procedure is basically an extended application of the Ford-Fulkerson dynamic flow algorithm which also solves the minimal cost flow problem. A simple example is included. The presence of bounded optimal are flows entertains the notion that one can pick a particular solution which is preferable by secondary criteria.     

Allocation of resources to offensive strategic weapon systems

In this paper a very versatile game model is developed for use in the long range planning of our strategic force posture. This highly aggregate model yields optimal force mixes for the triad (land- and sea-based missile systems and bombers) under a variety of constraints. The model described here is a survivability model; however, it is shown how the model can still be used as a measure of overall system effectiveness. Constraints imposed on the problem include both SALT and budget limitations.     

Optimal interdiction policy for a flow network

This paper analyzes the problem faced by a field commander who, confronted by an enemy on N battlefields, must determine an interdiction policy for the enemy's logistics system which minimizes the amount of war material flowing through this system per unit time. The resource utilized to achieve this interdiction is subject to constraint. It can be shown that this problem is equivalent to determining the set of arcs Z* to remove subject to constraint from a directed graph G such that the resulting maximal flow is minimized. A branch and bound algorithm for the solution to this problem is described, and a numerical example is provided.     

(R.Q) inventory problem with unknown mean demand and learning

We address a single product, continuous review model with stationary Poisson demand. Such a model has been effectively studied when mean demand is known. However, we are concerned with managing new items for which only a Bayesian prior distribution on the mean is available. As demand occurs, the prior is updated and our control parameters are revised. These include the reorder point (R) and reorder quantity (Q). Deemer, taking a clue from some earlier RAND work, suggested using a model appropriate for known mean, but using a Compound Poisson distribution for demand rather than Poisson to reflect uncertainty about the mean. Brown and Rogers also used this approach but within a periodic review context. In this paper we show how to compute optimum reorder points for a special problem closely related to the problem of real interest. In terms of the real problem, subject to a qualification to be discussed, the reorder points found are upper bounds for the optimum. At the same time, the reorder points found can never exceed those found by the Compound Poisson (Deemer) approach. And they can be smaller than those found when there is no uncertainty about the mean. As a check, the Compound Poisson and proposed approach are compared by simulation.     

Sequential determination of inspection epochs for reliability systems with general lifetime distributions

The problem of determining the optimal inspection epoch is studied for reliability systems in which N components operate in parallel. Lifetime distribution is arbitrary, but known. The optimization is carried with respect to two cost factors: the cost of inspecting a component and the cost of failure. The inspection epochs are determined so that the expected cost of the whole system per time unit per cycle will be minimized. The optimization process depends in the general case on the whole failure history of the system. This dependence is characterized. The cases of Weibull lifetime distributions are elaborated and illustrated numerically. The characteristics of the optimal inspection intervals are studied theoretically.     

The performance of cannibalization policies in a maintenance system with spares,repair, and resource constraints

This article presents the results of comparing the performance of several cannibalization policies using a simulation model of a maintenance system with spares, repair, and resource constraints. Although the presence of cannibalization has been incorporated into a number of maintenance system models reported in the literature, the questions of whether cannibalization should be done and what factors affect canibalization have received little attention. Policies tested include both no cannibalization and unlimited cannibalization as well as other based on the number of maintenance personnel available, the short-term machine failure rate at the time of cannibalization, and the relationship between the mean cannibalization and repair rates. The best policies found are those that allow cannibalization only when it can be done quickly relative to repair or when it can be done without delaying part repair actions. The policy of complete cannibalization (always cannibalize when it is possible) is found to perform poorly except when either average maintenance personnel utilization is very low or when mean cannibalization times are very short relative to mean repair times. The latter result casts doubts on the appropriateness of the assumption of complete cannibalization in many models in the literature.     

On the minimization of a certain convex function arising in applied decision theory

The author, in an expository paper [4], has presented an algorithm for choosing a non-negative vector

     

Restricted planar location problems and applications

Facility location problems in the plane are among the most widely used tools of Mathematical Programming in modeling real-world problems. In many of these problems restrictions have to be considered which correspond to regions in which a placement of new locations is forbidden. We consider center and median problems where the forbidden set is a union of pairwise disjoint convex sets. As applications we discuss the assembly of printed circuit boards, obnoxious facility location and the location of emergency facilities. © 1995 John Wiley & Sons, Inc.     

INCAPACITATING BIOCHEMICAL WEAPONS

Military interest in incapacitating biochemical weapons has grown in recent years as advances in science and technology have appeared to offer the promise of new “non-lethal” weapons useful for a variety of politically and militarily challenging situations. There is, in fact, a long and unfulfilled history of attempts to develop such weapons. It is clear that advances are opening up a range of possibilities for future biological and chemical weapons more generally. The treaties prohibiting biological and chemical weapons make no distinction between lethal and “non-lethal” weapons—all are equally prohibited. Indeed, a sharp and technically meaningful distinction between lethal and “non-lethal” biological and chemical weapons is beyond the capability of science to make. Thus, interest in incapacitating biochemical weapons, and efforts on the part of various states to develop them, pose a significant challenge to the treaty regimes, to the norms against biological and chemical warfare that they embody, and, ultimately, to the essential protections that they provide. Preventing a new generation of biological and chemical weapons from emerging will take concerted efforts and action at the local, national, and international levels.