War as a System: A Three-Stage Model for the Development of Clausewitz’s Thinking on Military Conflict and Its Constraints

This article presents a new model for the development of Carl von Clausewitz’s thinking on the factors that constrain warfare. The model posits three stages in his thinking that are determined by two system theoretic dimensions. The three stages are friction as a constraint on the effectiveness of the execution of military plans on paper, suspension as a constraint on the intensity of military action and political objectives as a constraint on military objectives. The two dimensions consist of an interactive perspective in the form of causal feedback loops and a holistic perspective in the form of a political system that forms the context of the military subsystem.     

Commitment decisions with partial information updating

In this paper, we extend the results of Ferguson M. Naval Research Logistics 8 . on an end‐product manufacturer's choice of when to commit to an order quantity from its parts supplier. During the supplier's lead‐time, information arrives about end‐product demand. This information reduces some of the forecast uncertainty. While the supplier must choose its production quantity of parts based on the original forecast, the manufacturer can wait to place its order from the supplier after observing the information update. We find that a manufacturer is sometimes better off with a contract requiring an early commitment to its order quantity, before the supplier commits resources. On the other hand, the supplier sometimes prefers a delayed commitment. The preferences depend upon the amount of demand uncertainty resolved by the information as well as which member of the supply chain sets the exchange price. We also show conditions where demand information updating is detrimental to both the manufacturer and the supplier. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

The multivariate Polya distribution in combat modeling

This paper investigates the multivariate Polya distribution (MPD) for application in combat models for which enemy targets must be randomly assigned to fighting units. Six sets of actual combat data motivate the allocation model. Scenarios include air‐to‐air combat, tank, and submarine warfare. Goodness of fit tests are derived which verify the validity of the MPD, and reinforce the notion that multinomial allocation is too simplistic for such combat models. Simulations to determine optimal allocations for minimal combat cost are applied in order to illustrate the role of the MPD in combat modeling. © 2001 John Wiley & Sons,Inc. Naval Research Logistics 48: 1–17, 2001     

Floor layouts using a multifacility location model

A procedure for obtaining a facilities scatter diagram within a rectangular boundary is developed using a multifacility location model. This method gives favorable computational results and has the advantage over other scatter diagram methods of being able to accommodate fixed facility locations. Examples illustrate how this method can be used by a designer/analyst either as a one-step algorithm or iteratively to build a layout.     

Concise RLT forms of binary programs: A computational study of the quadratic knapsack problem

The reformulation‐linearization technique (RLT) is a methodology for constructing tight linear programming relaxations of mixed discrete problems. A key construct is the multiplication of “product factors” of the discrete variables with problem constraints to form polynomial restrictions, which are subsequently linearized. For special problem forms, the structure of these linearized constraints tends to suggest that certain classes may be more beneficial than others. We examine the usefulness of subsets of constraints for a family of 0–1 quadratic multidimensional knapsack programs and perform extensive computational tests on a classical special case known as the 0–1 quadratic knapsack problem. We consider RLT forms both with and without these inequalities, and their comparisons with linearizations derived from published methods. Interestingly, the computational results depend in part upon the commercial software used. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Transportation problems with aggregated destinations when demands are uncertain

Transportation problems with uncertain demands are useful applied models themselves, and also they represent in a formal way the problem of estimating demands for use in deterministic models. We consider the effects of using a small, aggregate model of this type in place of a larger, more detailed one. Formulation of the aggregate objective function turns out to depend on how one chooses to use (disaggregate) the solution; several alternative methods are examined. Bounds are derived on the error induced by the approximation, thus facilitating comparison of alternative aggregations. We also consider the problem of estimating demands for an aggregate-level deterministic problem. In a specific sense, it is often not the case (as one might expect) that such aggregate demands are easier to estimate than the detailed demands. This is because aggregation and centralization are not the same thing.