Special Air Service Books to Choose From

Barry Davies, Joining the SAS: How to Get In and What It's Like.Miami: Lewis International Inc., 1998. Pp.214, photos, index. $22.95. ISBN 0–966771–4–2.

Peter McAleese and John Avery, McAleese's Fighting Manual: The Definitive Soldier's Handbook.London: Orion, 1998. Pp.179, illus. £18.95. ISBN 0–75280–063–9.

Steve Crawford et al.The SAS Encyclopedia: The Definitive Guide to the World's Crack Regiment.Miami: Lewis International Inc., 1998. Pp.288, photos, maps, index. $29.95. ISBN 0–9666771–0–2.

Barry Davies et al.The Complete Encyclopedia of the SAS.London: Virgin Publishing Ltd, 1998. Pp.288, photos, maps, no index. $39.95. ISBN 1–85227–707–6.     

List of contributors

This article examines Edward Lansdale's return to South Vietnam during the Johnson administration. Lansdale offered a persuasive critique of the mistakes the American policy in Vietnam, but his potential influence was severely limited by a combination of bureaucratic infighting in Saigon and a general indifference to the political aspects of the conflict in Washington. While Lansdale was unable to signiflcantly influence the policies of the Johnson administration, his experience in Saigon during 1965–68 offers historians a unique perspective on many facets of American and South Vietnamese policymaking during a crucial period of the Vietnam War.     

Institutionalizing supreme command: explaining political–military integration in the Vietnam War, 1964–1968

Under what conditions can leaders achieve wartime political–military integration? In the Vietnam War, political–military integration exhibited dramatic variation: in the air war, the US was able to tightly integrate its political objectives and military conduct, but in the ground war, the American military prosecuted a strategy that was both divorced from broader political objectives and was immune from Washington's influence. I argue that the nature of information management between the military and civilian leadership explains the pattern of political–military integration in the Vietnam War more completely than do explanations that focus on the organizational cultures of professional militaries.     

Why did Sudan Lose a small war in Southern Sudan?

ABSTRACT

When on the wrong end of an asymmetry in the projection of hard power, weaker sides countenance the grim arithmetic of avoiding direct and massed confrontations. Invariably, insurgents have over the ages tended to employ indirect tactical methods to render their stronger opponents ineffective. Ultimately – interest asymmetry, regime type, asymmetries of strategy, and external intervention – combine in a complex interplay and pattern, to militate against a strong side. In Sudan, these factors interacted throughout the civil wars to produce regional autonomy and finally an independent South Sudan in 2011. Similar strategic logic had confronted many large African states battling insurgencies in Ethiopia, Angola, Nigeria, Zaire, and apartheid-era South Africa. Oftentimes, weakening public resolve has caused these governments to accommodate, capitulate or withdraw even if they try not to blink. Notwithstanding the regime type, it can be concluded that the majority of strong actors are prone to fail in a protracted, asymmetric conflict. Hence, the notion of linking victory in counterinsurgency to the degree of openness (democratic polyarchies); or closeness (totalitarianism) – is still valid but highly contestable in the case of Africa’s large dysfunctional states.     

Bounding methods for facilities location algorithms

Single- and multi-facility location problems are often solved with iterative computational procedures. Although these procedures have proven to converage, in practice it is desirable to be able to compute a lower bound on the objective function at each iteration. This enables the user to stop the iterative process when the objective function is within a prespecified tolerance of the optimum value. In this article we generalize a new bounding method to include multi-facility problems with l_p distances. A proof is given that for Euclidean distance problems the new bounding procedure is superior to two other known methods. Numerical results are given for the three methods.     

Estimating the accuracy of the coverages of outer β-content tolerance intervals,which control both tails of the normal distribution

Tolerance limits which control both tails of the normal distribution so that there is no more than a proportion β₁ in one tail and no more than β₂ in the other tail with probability γ may be computed for any size sample. They are computed from X? - k₁S and X? - k₂S, where X? and S are the usual sample mean and standard deviation and k₁ and k₂ are constants previously tabulated in Odeh and Owen [3]. The question addressed is, “Just how accurate are the coverages of these intervals (– Infin;, X? – k₁S) and (X? + k₂S, ∞) for various size samples?” The question is answered in terms of how widely the coverage of each tail interval differs from the corresponding required content with a given confidence γ′.     

An efficient primal approach to bottleneck transportation problems

This article addresses bottleneck linear programming problems and in particular capacitated and constrained bottleneck transportation problems. A pseudopricing procedure based on the poly-ω procedure is used to facilitate the primal simplex procedure. This process allows the recent computational developments such as the Extended Threaded Index Method to be applied to bottleneck transportation problems. The impact on problem solution times is illustrated by computational testing and comparison with other current methods.     

Exact first and second order moments of order statistics from the truncated exponential distribution

Exact expressions for the first and second order moments of order statistics from the truncated exponential distribution, when the proportion 1–P of truncation is known in advance, are presented in this paper. Tables of expected values and variances-covariances are given for P = 0.5 (0.1) 0.9 and n = 1 (1) 10.