‘Mad Dog?’ Samuel Huntington and the Vietnam War

Harvard professor Samuel P. Huntington has frequently been considered a Vietnam War hawk. His observation that ‘forced-draft urbanization’ might help the United States win the war has come to define his engagement in contemporary strategic debates. This essay argues that both Huntington’s academic work and his private policy advice to the U.S. Government in fact urged a political settlement to the conflict. It argues that in spite of this, Huntington refused to break publicly with the U.S. policy because of his wider concern over what he saw as a crisis of authority in the U.S. foreign policy and governing institutions in the era.     

Effective in battle: conceptualizing soldiers’ combat effectiveness*

How do we understand combat effectiveness – soldiers’ performance in battle? Despite the broad consensus that understanding combat effectiveness is important both for scholars and policymakers, there is widespread disagreement about what combat effectiveness is. More specifically, studies of effectiveness tend to focus on either the skill of soldiers in battle, or their will to fight. Yet both skill and will are essential components of an effective fighting force. This article argues that understanding combat effectiveness requires understanding both of these key components of effectiveness. In other words, combat effectiveness requires both the skill and will to engage the enemy in an organized manner. It then demonstrates the usefulness of this conceptualization by applying it to the cases of British, Indian, and Australian forces fighting the Japanese during the Second World War. Only when scholars are talking about the same concept will our understanding of the conditions under which militaries are effective in battle progress. By comparing different units fighting the same opponent under the same material conditions, I demonstrate that units vary both in their combat skill and their will to fight, and that understanding their effectiveness in battle requires analyzing both of these key factors.     

Heterogeneous multitrunking queueing systems with thresholds

Queueing systems with multiple servers are commonly used to model telecommunications systems. But, in general, the service rate of each of the servers is not the same. This fact is indeed true in a communication network where one path (server) may be a terrestrial link and the other (server) a satellite link with its inherent propagation delay. In this article we consider a two-server system where arriving customers are first placed in the queue for the faster server until that queue size reaches a certain threshold, whereupon they are diverted to the slower server. Additional arriving customers are assigned to the slower server until the faster server's queue drops to another lower threshold, at which point arrivals are reassigned to the faster server. We develop an exact mathematical model of the steady-state behavior of each queueing system and a simple analytic approximation.     

Minimizing flow time on a single machine with job classes and setup times

We examine the static sequencing problem of ordering the processing of jobs on a single machine so as to minimize the average weighted flow time. It is assumed that all jobs have zero ready times, and that the jobs are grouped into classes with the property that setup tasks are only required when processing switches from jobs of one class to jobs of another class. The time required for each setup task is given by the sum of a setdown time from the previous class and a setup time for the new class. We show that an algorithm presented in the literature for solving a special case of this problem gives suboptimal solutions. A number of properties of the optimal solution are derived, and their use in algorithms is evaluated. Computational results are presented for both a branch-and-bound procedure and a simpler depth-first search.     

Tests for transient means in simulated time series

We present a family of tests to detect the presence of a transient mean in a simulation process. These tests compare variance estimators from different parts of a simulation run, and are based on the methods of batch means and standardized time series. Our tests can be viewed as natural generalizations of some previously published work. We also include a power analysis of the new tests, as well as some illustrative examples. © 1994 John Wiley & Sons, Inc.     

A simulated annealing approach to the cyclic staff-scheduling problem

This article presents the application of a simulated annealing heuristic to an NP-complete cyclic staff-scheduling problem. The new heuristic is compared to branch-and-bound integer programming algorithms, as well as construction and linear programming-based heuristics. It is designed for use in a continuously operating scheduling environment with the objective of minimizing the number of employees necessary to satisfy forecast demand. The results indicate that the simulated annealing-based method tends to dominate the branch-and-bound algorithms and the other heuristics in terms of solution quality. Moreover, the annealing algorithm exhibited rapid convergence to a low-cost solution. The simulated annealing heuristic is executed in a single program and does not require mathematical programming software. © 1993 John Wiley & Sons, Inc.     

The maximum collection problem with time-dependent rewards

We consider a routing problem where the objective is to maximize the sum of the rewards collected at the nodes visited. Node rewards are decreasing linear functions of time. Time is spent when traveling between pairs of nodes, and while visiting the nodes. We propose a penalty-based greedy (heuristic) algorithm and a branch-and-bound (optimal) algorithm for this problem. The heuristic is very effective in obtaining good solutions. We can solve problems with up to 20 nodes optimally on a microcomputer using the branch-and-bound algorithm. We report our computational experience with this problem. © 1996 John Wiley & Sons, Inc.     

Note: A local-search heuristic for large set-covering problems

In this note we describe a local-search heuristic (LSH) for large non-unicost set-covering problems (SCPs). The new heuristic is based on the simulated annealing algorithm and uses an improvement routine designed to provide low-cost solutions within a reasonable amount of CPU time. The solution costs associated with the LSH compared very favorably to the best previously published solution costs for 20 large SCPs taken from the literature. In particular, the LSH yielded new benchmark solutions for 17 of the 20 test problems. We also report that, for SCPs where column cost is correlated with column coverage, the new heuristic provides solution costs competitive with previously published results for comparable problems. © 1995 John Wiley & Sons, Inc.