Unrestricted warfare: Review essay I

During the Nigerian Civil War (1967–1970), France chose to support Biafra, but only on a limited scale, providing mercenaries and obsolete weaponry to Ojukwu's regime. General Charles de Gaulle's assistance to Ojukwu was conditioned by the French military drawdown after 1961, the increased power of French secret services on the continent, and the interventions in Katanga (1960–1963), Gabon (1964) and Chad (1968–1972). France supported Biafra primarily to protect its former colonies from Nigeria, stop Soviet subversion and acquire an economic foothold in the oil-rich Niger Delta. De Gaulle chose a limited strategy for two reasons. If Biafra won the war, France would be Biafra's greatest ally. If Nigeria won the war, France could extricate itself from the situation relatively easily and re-establish relations with the Nigerian government, which is what ultimately occurred.     

Comparison between constant‐stress and step‐stress accelerated life tests under Time Constraint

By running life tests at higher stress levels than normal operating conditions, accelerated life testing (ALT) quickly yields information on the lifetime distribution of a test unit. The lifetime at the design stress is then estimated through extrapolation using a regression model. In constant‐stress testing, a unit is tested at a fixed stress level until failure or the termination time point of test, whereas step‐stress testing allows the experimenter to gradually increase the stress levels at some prefixed time points during the test. In this work, the optimal k‐level constant‐stress and step‐stress ALTs are compared for the exponential failure data under complete sampling and Type‐I censoring. The objective is to quantify the advantage of using the step‐stress testing relative to the constant‐stress one. Assuming a log‐linear life–stress relationship with the cumulative exposure model for the effect of changing stress in step‐stress testing, the optimal design points are determined under C/D/A‐optimality criteria. The efficiency of step‐stress testing to constant‐stress one is then discussed in terms of the ratio of optimal objective functions based on the information matrix. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 00: 000–000, 2013     

One size does not fit all: personalized incentives in military compensation

A critical element in implementing a compensation scheme including nonmonetary incentives (NMIs) is recognizing that preferences vary widely across Service members. There are at least three sources of variability: across different population classes, across individuals within a population class, and across NMI packages for a particular individual. Surveys across different military communities, ranks, and years of Service show the difficulty of identifying any NMI that has significant value for even 50% of the active duty force. At the same time, approximately 80% of the surveyed Service members expressed a significant positive value for at least one NMI. Therefore, one-size-fits-all incentive packages will not be nearly as effective as more personalized incentive packages. The authors discuss variability in Service member NMI preferences and outline an approach to implementing personalized NMI packages in military compensation through a sealed-bid reverse auction, where Service members select individual NMIs from a “cafeteria-style” menu of options.     

Algorithms for the minimax transportation problem

In this paper, we consider a variant of the classical transportation problem as well as of the bottleneck transportation problem, which we call the minimax transportation problem. The problem considered is to determine a feasible flow x_ij from a set of origins I to a set of destinations J for which max_(i,j)εIxJ{c_ijx_ij} is minimum. In this paper, we develop a parametric algorithm and a primal-dual algorithm to solve this problem. The parametric algorithm solves a transportation problem with parametric upper bounds and the primal-dual algorithm solves a sequence of related maximum flow problems. The primal-dual algorithm is shown to be polynomially bounded. Numerical investigations with both the algorithms are described in detail. The primal-dual algorithm is found to be computationally superior to the parametric algorithm and it can solve problems up to 1000 origins, 1000 destinations and 10,000 arcs in less than 1 minute on a DEC 10 computer system. The optimum solution of the minimax transportation problem may be noninteger. We also suggest a polynomial algorithm to convert this solution into an integer optimum solution.     

The asymptotic joint distribution of the state occupancy times in an alternating renewal process

An alternating renewal process starts at time zero and visits states 1,2,…,r, 1,2, …,r 1,2, …,r, … in sucession. The time spent in state i during any cycle has cumulative distribution function F_i, and the sojourn times in each state are mutually independent, positive and nondegenerate random variables. In the fixed time interval [0,T], let U_i(T) denote the total amount of time spent in state i. In this note, a central limit theorem is proved for the random vector (U_i(T), 1 ≤ i ≤ r) (properly normed and centered) as T → ∞.