COIN fights: A response to Etzioni

Etzioni both exaggerates and minimizes the influence of my book Learning to Eat Soup with a Knife on different components of US military doctrine, mischaracterizes my treatment of the Malayan Emergency, and unfairly denigrates the successes of counterinsurgency in Iraq from 2007 to 2011 while misattributing the reasons for its failures in both Iraq and Afghanistan.     

Lanchester-type models of warfare and optimal control

The optimization of the dynamics of combat (optimal distribution of fire over enemy target types) is studied through a sequence of idealized models by use of the mathematical theory of optimal control. The models are for combat over a period of time described by Lanchester-type equations with a choice of tactics available to one side and subject to change with time. The structure of optimal fire distribution policies is discussed with reference to the influence of combatant objectives, termination conditions of the conflict, type of attrition process, and variable attrition-rate coefficients. Implications for intelligence, command and control systems, and human decision making are pointed out. The use of such optimal control models for guiding extensions to differential games is discussed.     

A note on the strategy of restriction and degenerate linear programming problems

Using the general computational strategy of restriction, necessary conditions for optimality provide an alternative criterion for entering variables when degeneracies arises in linear programming problems. Although cycling may still occur, it is shown that if it is possible to make progress at the next iteration, the criterion is guaranteed to identify a non-basic variable which increases the value of the basic solution, thereby reducing stalling. An alternative method for determining variables to exit the basis when degeneracies occur is also suggested.     

Landmarks in defense literature

The Cavalry Goes Through. By Bernard Newman. Henry Holt, New York (1930)     

Mean residual life of coherent systems consisting of multiple types of dependent components

Mean residual life is a useful dynamic characteristic to study reliability of a system. It has been widely considered in the literature not only for single unit systems but also for coherent systems. This article is concerned with the study of mean residual life for a coherent system that consists of multiple types of dependent components. In particular, the survival signature based generalized mixture representation is obtained for the survival function of a coherent system and it is used to evaluate the mean residual life function. Furthermore, two mean residual life functions under different conditional events on components’ lifetimes are also defined and studied.     

A simple and untraditional analysis of western alliance burden‐sharing

The original Olson and Zeckhauser model of alliance burden‐sharing was based on the following four assumptions: (1) alliance defence is a pure public good; (2) allied nations make their security contribution decisions without consulting the other allies; (3) alliances produce only a single public good; and (4) alliance defence is produced with equal degrees of efficiency in all alliance nations. But while the first of these assumptions has received a great deal of attention in the alliance literature, the remaining ones have received comparatively less attention, particularly in terms of empirical analyses. This paper synthesizes a varied literature developed around these four assumptions, both substantively and theoretically, and shows that when these assumptions are brought closer to real world approximations, hypotheses regarding the potential for security cooperation with less free‐riding result. This article also provides a simple test of Western alliance burden‐sharing in the areas of military spending, development resources spending, and research and development spending that supports the hypothesis positing more equitable burden‐sharing.     

An algorithm for solving general fractional interval programming problems

A Linear Fractional Interval Programming problem (FIP) is the problem of extremizing a linear fractional function subject to two-sided linear inequality constraints. In this paper we develop an algorithm for solving (FIP) problems. We first apply the Charnes and Cooper transformation on (FIP) and then, by exploiting the special structure of the pair of (LP) problems derived, the algorithm produces an optimal solution to (FIP) in a finite number of iterations.