A rent‐seeking model of international competition and alliances∗

This paper presents an alternative approach for analyzing international competition and alliances as rent‐seeking contests that are able to capture the impure public good nature of defense spending. Two‐country Cournot and Stackelberg games are considered and comparative static results derived. A three‐country model is investigated, and alliance behavior is explored in the context of this rent‐seeking model. The conjecture that an alliance may become less effective if the allies’ interests become more closely aligned is verified. Finally, the model is generalized, and a Nash‐Cournot equilibrium is computed.     

Threshold optimization for weighted voting classifiers

Weighted voting classifiers considered in this paper consist of N units each providing individual classification decisions. The entire system output is based on tallying the weighted votes for each decision and choosing the one which has total support weight exceeding a certain threshold. Each individual unit may abstain from voting. The entire system may also abstain from voting if no decision support weight exceeds the threshold. Existing methods of evaluating the reliability of weighted voting systems can be applied to limited special cases of these systems and impose some restrictions on their parameters. In this paper a universal generating function method is suggested which allows the reliability of weighted voting classifiers to be exactly evaluated without imposing constraints on unit weights. Based on this method, the classifier reliability is determined as a function of a threshold factor, and a procedure is suggested for finding the threshold which minimizes the cost of damage caused by classifier failures (misclassification and abstention may have different price.) Dynamic and static threshold voting rules are considered and compared. A method of analyzing the influence of units' availability on the entire classifier reliability is suggested, and illustrative examples are presented. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 322–344, 2003.     

How long until midnight? Intelligence-policy relations and the United States response to the Israeli nuclear program, 1959–1985

Why did the United States fail to stop Israeli acquisition of nuclear weapons? Existing research argues that patrons such as the U.S. should have an easy time halting proliferation by militarily and economically vulnerable clients. Nevertheless, Israel acquired nuclear weapons with relatively little American opposition. Utilizing extensive primary source research, we argue that problematic intelligence-policy relations hindered U.S. efforts to arrest Israeli proliferation as (1) policymakers often gave mixed guidance to the intelligence community, resulting in (2) limited information on Israeli efforts that reinforced policy ambiguity. The results carry implications for understanding the dynamics of nuclear proliferation and intelligence-policy relations.     

Compromise allocation in multivariate stratified sampling: An integer solution

The problem of determining the sample sizes in various strata when several characteristics are under study is formulated as a nonlinear multistage decision problem. Dynamic programming is used to obtain an integer solution to the problem. © 1997 John Wiley & Sons, Inc.     

Optimizing submarine berthing with a persistence incentive

Submarine berthing plans reserve mooring locations for inbound U.S. Navy nuclear submarines prior to their port entrance. Once in port, submarines may be shifted to different berthing locations to allow them to better receive services they require or to make way for other shifted vessels. However, submarine berth shifting is expensive, labor intensive, and potentially hazardous. This article presents an optimization model for submarine berth planning and demonstrates it with Naval Submarine Base, San Diego. After a berthing plan has been approved and published, changed requests for services, delays, and early arrival of inbound submarines are routine events, requiring frequent revisions. To encourage trust in the planning process, the effect on the solution of revisions in the input is kept small by incorporating a persistence incentive in the optimization model. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 301–318, 1997.     

Incorporating learning curve costs in acquisition strategy optimization

Each year, the U.S. Army procures billions of dollars worth of weapons and equipment. The process of deciding what to buy, when to buy, and in what quantities is extremely complex, requiring extensive analysis. Two techniques used in this analysis are mathematical programming and cost estimation. Although they are related through constraints on available procurement funds, the use of nonlinear cost learning curves, which better represent system costs as a function of quantity produced, have not been incorporated into the mathematical programming formulations that compute the quantities of items to be procured. As a result, the solutions obtained could be either suboptimal, or even infeasible with respect to budgetary limitations. In this paper we present a piecewise linear approximation of the learning curve costs for a more accurate portrayal of budgetary constraints used in a mixed integer linear programming for acquisition strategy optimization. In addition, implementation issues are discussed, and performance results are given. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 255–271, 1999     

Setting military reenlistment bonuses

The United States military frequently has difficulty retaining enlisted personnel beyond their initial enlistment. A bonus program within each service, called a Selective Reenlistment Bonus (SRB) program, seeks to enhance reenlistments and thus reduce personnel shortages in critical military occupational specialties (MOSs). The amount of bonus is set by assigning “SRB multipliers” to each MOS. We develop a nonlinear integer program to select multipliers which minimize a function of deviations from desired reenlistment targets. A Lagrangian relaxation of a linearized version of the integer program is used to obtain lower bounds and feasible solutions. The best feasible solution, discovered in a coordinate search of the Lagrangian function, is heuristically improved by apportioning unexpended funds. For large problems a heuristic variable reduction is employed to speed model solution. U.S. Army data and requirements for FY87 yield a 0-1 integer program with 12,992 binary variables and 273 constraints, which is solved within 0.00002% of optimality on an IBM 3033AP in less than 1.7 seconds. More general models with up to 463,000 binary variables are solved, on average, to within 0.009% of optimality in less than 1.8 minutes. The U.S. Marine Corps has used a simpler version of this model since 1986. © 1993 John Wiley & Sons, Inc.     

A bivariate pareto model and its applications to reliability

We consider a bivariate Pareto distribution, as a generalization of the Lindley-Singpurwalla model, by incorporating the influence of the operating conditions on a two-component dependent system. The properties of the model and its applications to reliability analysis are discussed. © 1993 John Wiley & Sons, Inc.