Optimal project compression with due-dated events

The paper proposes an algorithm for the determination of the solution of the activities to be shortened and the amount by which they are to be shortened in order to minimize the total cost of project completion. This cost involves a linear penalty for tardienss of a set of key events and a linear cost of activity compression from its normal duration. The procedure is a generalization of the work of Fulkerson.     

Design of a process control scheme for defects per 100 units based on aoql

A process control scheme is developed in which decisions as to the frequency of sampling are made based upon the choice of an Average Outgoing Quality Limit. The scheme utilizes plotted points on a U-control chart for defects and the theory of runs to determine when to switch among Reduced, Normal, Tightened, and 100 percent inspection. The scheme is formulated as a semi-Markov process to derive steady stale equations for the probabilities of being in Reduced, Normal, Tightened, or 100 percent inspection and for Average Outgoing Quality and Average Fraction Inspected. The resulting system and the computer programs used to derive it are discussed.     

Optimal number of minimal repairs before replacement of a system subject to shocks

A system is subject to shocks that arrive according to a nonhomogeneous Poisson process. As shocks occur a system has two types of failures. Type 1 failure (minor failure) is removed by a minimal repair, whereas type 2 failure (catastrophic failure) is removed by replacement. The probability of a type 2 failure is permitted to depend on the number of shocks since the last replacement. A system is replaced at the times of type 2 failure or at the nth type 1 failure, whichever comes first. The optimal policy is to select n* to minimize the expected cost per unit time for an infinite time span. A numerical example is given to illustrate the method. © 1996 John Wiley & Sons, Inc.     

Two‐stage component test plans for testing the reliability of a series system

A system reliability is often evaluated by individual tests of components that constitute the system. These component test plans have advantages over complete system based tests in terms of time and cost. In this paper, we consider the series system with n components, where the lifetime of the i‐th component follows exponential distribution with parameter λ_i. Assuming test costs for the components are different, we develop an efficient algorithm to design a two‐stage component test plan that satisfies the usual probability requirements on the system reliability and in addition minimizes the maximum expected cost. For the case of prior information in the form of upper bounds on λ_i's, we use the genetic algorithm to solve the associated optimization problems which are otherwise difficult to solve using mathematical programming techniques. The two‐stage component test plans are cost effective compared to single‐stage plans developed by Rajgopal and Mazumdar. We demonstrate through several numerical examples that our approach has the potential to reduce the overall testing costs significantly. © 2002 John Wiley & Sons, Inc. Naval Research Logistics, 49: 95–116, 2002; DOI 10.1002/nav.1051     

The relationship between material failures and flight hours

If material failures follow a Poisson distribution, then the expected number of failures is exactly proportional to flight hours. However, this article demonstrates that proportionality will not be revealed by simple correlation or regression analysis between monthly flight hours and the number of monthly failures. To test for proportionality, one must instead test the underlying hypothesis that the data follow a Poisson distribution. This article presents three simple tests that may be used for this purpose. The Poisson distribution requires that the mean and variance of the number of failures be equal. This article suggests several alternative models that may be used for samples in which the variance exceeds the mean. First, the mean of the Poisson distribution may itself be randomly distributed across the observational units according to a gamma distribution. If so, the number of failures will have a negative binomial distribution. Second, the mean of the Poisson distribution may depend systematically upon a set of observable explanatory variables. In this case, the Poisson regression model is appropriate. Finally, the mean of the Poisson distribution may contain both a systematic component that depends upon observable variables and a random component. This situation yields a generalized Poisson regression model.     

Reactor-grade plutonium and nuclear weapons: ending the debate

The claim that reactor-grade plutonium cannot or will not be used to produce nuclear weapons has been used to justify non-nuclear-weapon states’ large stockpiles of plutonium that has been separated from highly radioactive spent fuel. However, by using reduced-mass plutonium cores, it is possible to manufacture reliable nuclear weapons with reactor-grade plutonium. These weapons can have the same design, size, weight, and predetonation probability as weapons using weapon-grade plutonium and would require no special cooling. The increased radiation from reactor-grade plutonium could be easily managed by shielding and operational procedures. Weapons using plutonium routinely produced by pressurized-water reactors could have a lethal area between 40 percent and 75 percent that of weapons using weapon-grade plutonium. In the past, both Sweden and Pakistan considered using reactor-grade plutonium to produce nuclear weapons, and India may be using reactor-grade plutonium in its arsenal today. Despite claims to the contrary, the United States used what was truly reactor-grade plutonium in a successful nuclear test in 1962. The capability of reactor-grade plutonium to produce highly destructive nuclear weapons leads to the conclusion that the separation of plutonium, plutonium stockpiling, and the use of plutonium-based fuels must be phased out and banned.     

Financial versus human resources in the Greek‐Turkish arms race: A forecasting investigation using artificial neural networks

This paper aims at forecasting the burden on the Greek economy resulting from the arms race against Turkey and at concentrating on the leading determinants of this burden. The military debt and the defence share of GDP are employed alternatively in order to approximate the measurement of the arms race pressure on Greece, and the method used is that of artificial neural networks. The use of a wide variety of explanatory variables in combination with the promising results derived, suggest that the impact on the Greek economy resulting from this arms race is determined, to a large, extent, by demographic factors which strongly favour the Turkish side. Prediction on both miltary debt and defence expenditure exhibited highly satisfactory accuracy, while the estimation of input significance, indicates that variables describing the Turkish side are often dominant over the corresponding Greek ones.     

Deterring the Undeterrable: Coercion,Denial, and Delegitimization in Counterterrorism

This article argues that deterrence theory can be applied to counterterrorism. Doing so requires broadening the traditional concept of deterrence by punishment, expanding deterrence by denial to include defense, mitigation, and strategic hindrance, and developing deterrence by delegitimization to influence the political, ideological, and religious rationales informing terrorist behavior. In practice, deterring terrorism requires tailoring threats against state and individual facilitators, diffusing the intended consequences of terrorism, and manipulating terrorist self–restraints. When these and other deterrent leverages are applied simultaneously against various actors and processes involved in terrorism, coercion can be achieved.     

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