Testing or fault-finding for reliability growth: A missile destructive-test example

A new piece of equipment has been purchased in a lot of size m. Some of the items can be used in destructive testing before the item is put into use. Testing uncovers faults which can be removed from the remaining pieces of equipment in the lot. If t < m pieces of equipment are tested, then those that remain, m₁ = m − t, have reduced fault incidence and are more reliable than initially, but m₁ may be too small to be useful, or than is desirable. In this paper models are studied to address this question: given the lot size m, how to optimize by choice of t the effectiveness of the pieces of equipment remaining after the test. The models used are simplistic and illustrative; they can be straightforwardly improved. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 623–637, 1997     

A finite algorithm for concave minimization over a polyhedron

We present a new algorithm for solving the problem of minimizing a nonseparable concave function over a polyhedron. The algorithm is of the branch-and-bound type. It finds a globally optimal extreme point solution for this problem in a finite number of steps. One of the major advantages of the algorithm is that the linear programming subproblems solved during the branch-and-bound search each have the same feasible region. We discuss this and other advantages and disadvantages of the algorithm. We also discuss some preliminary computational experience we have had with our computer code for implementing the algorithm. This computational experience involved solving several bilinear programming problems with the code.     

Size Still Matters: Explaining Sri Lanka’s Counterinsurgency Victory over the Tamil Tigers

The military effectiveness literature has largely dismissed the role of material preponderance in favor of strategic interaction theories. The study of counterinsurgency, in which incumbent victory is increasingly rare despite material superiority, has also turned to other strategic dynamics explanations like force employment, leadership, and insurgent/adversary attributes. Challenging these two trends, this paper contends that even in cases of counterinsurgency, material preponderance remains an essential—and at times the most important—factor in explaining battlefield outcomes and effectiveness. To test this, the paper turns to the case of the Sri Lankan state’s fight against the Tamil Tiger insurgency, a conflict which offers rich variation over time across six periods and over 25 years. Drawing on evidence from historical and journalistic accounts, interviews, memoirs, and field research, the paper demonstrates that material preponderance accounts for variation in military effectiveness and campaign outcomes (including military victory in the final campaign) better than strategic explanations. Additionally, a new quantitative data-set assembled on annual loss-exchange ratios demonstrates the superiority of materialist explanations above those of skill, human capital, and regime type.