State information lag markov decision process with control limit rule

In the framework of a discrete Markov decision process with state information lag, this article suggests a way for selecting an optimal policy using the control limit rule. The properties sufficient for an optimal decision rule to be contained in the class of control limit rules are also studied. The degradation in expected reward from that of the perfect information process provides a measure of the potential value of improving the information system.     

An application of empirical bayes techniques to the simultaneous estimation of many probabilities

Consider the following situation: Each of N different combat units is presented with a number of requirements to satisfy, each requirement being classified into one of K mutually exclusive categories. For each unit and each category, an estimate of the probability of that unit satisfying any requirement in that category is desired. The problem can be generally stated as that of estimating N different K-dimensional vectors of probabilities based upon a corresponding set of K-dimensional vectors of sample proportions. An empirical Bayes model is formulated and applied to an example from the Marine Corps Combat Readiness Evaluation System (MCCRES). The EM algorithm provides a convenient method of estimating the prior parameters. The Bayes estimates are compared to the ordinary estimates, i.e., the sample proportions, by means of cross validation, and the Bayes estimates are shown to provide considerable improvement.     

Book Reviews

National Security Concepts of States: New Zealand. By Kennedy Graham. Taylor & Francis, London (1989), ISBN 0-8448-1614-0, £27.00

Power and Prestige in the British Army. By R.G. L. von Zugbach. Gower, Aldershot (1988), ISBN 0-566-05561-9, £22.50

The American Civil War and the Origins of Modern Warfare—Ideas, Organization, and Field Command. By Edward Hagerman. Indiana University Press, Bloomington, IN (1988), ISBN 0-253-30546-2, $37.50 (£23.29)

British Seapower and Procurement between the Wars: a Reappraisal of Rearmament. By G. A. H. Gordon. Macmillan, London (1988), ISBN 0-333-42332-1. £29.50

Armies in Low-intensity Conflict: a Comparative Analysis. Edited by David A. Charters and Maurice Tugwell. Brassey's Defence Publishers, London (1989), ISBN 0-08-036253-2, £25.00 ($45.00); Deadly Paradigms: the Failure of U.S. Counterinsurgency Policy. By Michael Shafer, Leicester University Press, Leicester (1988), ISBN 0-7185-1311-8, £28.00

British Defence Policy Striking the Right Balance. By J. Baylis. Macmillan, London (1989), ISBN 0-333-49133-5, £29.50 or £9.99     

The discrete max-min problem

The historic max-min problem is examined as a discrete process rather than in its more usual continuous mode. Since the practical application of the max-min model usually involves discrete objects such as ballistic missiles, the discrete formulation of the problem seems quite appropriate. This paper uses an illegal modification to the dynamic programming process to obtain an upper bound to the max-min value. Then a second but legal application of dynamic programming to the minimization part of the problem for a fixed maximizing vector will give a lower bound to the max-min value. Concepts of optimal stopping rules may be applied to indicate when sufficiently near optimal solutions have been obtained.     

Relationships among potential sorties,ground support,and aircraft reliability

A methodology is developed for assessing tactical airfield/aircraft system effectiveness, and for evaluating effectiveness changes resulting from incremental investments in ground support resources and/or aircraft reliability. Two categories of ground support functions–turnaround and maintenance–are distinguished. The measure of effectiveness is the maximum potential sortie rate achievable by the system. The methodology enables empirical derivation of the general equation of the tactical airfield/aircraft system. It also enables graphical presentation of the system tradeoffs in the form of a System Analysis Chart.     

Suboptimal algorithms for the quadratic assignment problem

The idea of combining relatively simple continuous methods with discrete procedures is used for the construction of suboptimal algorithms for quadratic assignment problems. Depending on the nature of the special problem these steps may vary in complexity. The simplest procedures require minimum storage space and result in tolerable computation times. Different choices of parameters and random variations may be used in order to obtain statistical distributions of suboptimal solutions. Computational results for sample problems indicate improvements on results of Steinberg, Gilmore, and Hillier and Connors.     

Optimal state-dependent pricing policies for a class of stochastic multiunit service systems

This paper models a k-unit service system (e.g., a repair, maintenance, or rental facility) with Poisson arrivals, exponential service times, and no queue. If we denote the number of units that are busy as the state of the system, the state-dependent pricing model formalizes the intuitive notion that when most units are idle, the price (i.e., the service charge per unit time) should be low, and when most units are busy, the price should be higher than the average. A computationally efficient algorithm based on a nonlinear programming formulation of the problem is provided for determination of the optimal state-dependent prices. The procedure ultimately reduces to the search on a single variable in an interval to determine the unique intersection point of a concave increasing function and a linear decreasing function. The algorithm takes, on the average, only about 1/2 second per problem on the IBM 360/65 (FORTRAN G Compiler). A discrete optimal-control approach to the problem is shown to result in essentially the same procedure as the nonlinear-programming formulation. Several properties of the optimal state-dependent prices are given. Comparisons of the optimal values of the objective function for the state-dependent and state-independent pricing policies show that the former is on the average, only about 0.7% better than the latter, which may explain partly why state-dependent pricing is not prevalent in many service systems. Potential generalizations of the model are discussed.