The dynamic transportation problem: A survey

The dynamic transportation problem is a transportation problem over time. That is, a problem of selecting at each instant of time t, the optimal flow of commodities from various sources to various sinks in a given network so as to minimize the total cost of transportation subject to some supply and demand constraints. While the earliest formulation of the problem dates back to 1958 as a problem of finding the maximal flow through a dynamic network in a given time, the problem has received wider attention only in the last ten years. During these years, the problem has been tackled by network techniques, linear programming, dynamic programming, combinational methods, nonlinear programming and finally, the optimal control theory. This paper is an up-to-date survey of the various analyses of the problem along with a critical discussion, comparison, and extensions of various formulations and techniques used. The survey concludes with a number of important suggestions for future work.     

The United States Coast Guard Computer-Assisted Search Planning system (CASP)

This paper provides an overview of the Computer-Assisted Search Planning (CASP) system developed for the United States Coast Guard. The CASP information processing methodology is based upon Monte Carlo simulation to obtain an initial probability distribution for target location and to update this distribution to account for drift due to currents and winds. A multiple scenario approach is employed to generate the initial probability distribution. Bayesian updating is used to reflect negative information obtained from unsuccessful search. The principal output of the CASP system is a sequence of probability “maps” which display the current target location probability distributions throughout the time period of interest. CASP also provides guidance for allocating search effort based upon optimal search theory.     

Recurrence relations between moments of order statistics

A general result for obtaining recurrence relations between single moments of order statistics is obtained and has been used to establish the recurrence relations between moments of some doubly truncated distributions. The examples considered are Weibull, exponential, Pareto, power function, Cauchy, and logistic. Recurrence relations are also obtained for nontruncated gamma and beta distributions.     

Book reviews

America's Secret Power: the CIA in a Democratic Society. By Loch K. Johnson. Oxford University Press, New York (1989), ISBN 0–19–505490–3, $24.95

The Bundeswehr and Western Security. Edited by Stephen F. Szabo. Houndmills, Basingstoke, and Macmillan, London (1990), ISBN 0–333–49880–1, £45.00

Symbolic Defense: the Cultural Significance of the Strategic Defense Initiative. By Edward Tabor Linenthal. University of Illinois Press, Chicago, IL (1989), ISBN 0–252–01619‐X, $19.95

Rethinking European Security. Edited by Furio Cerutti and Rodolfo Ragionieri. Crane Russak, New York (1990), £29.00

Alternative Conventional Defense Postures in the European Theater, Vol. 1: The Military Balance and Domestic Constraints. Edited by Hans Günter Brauch and Robert Kennedy, Crane Russak, New York (1990), £32.00

The Gulf War. Edited by Hanns Maull and Otto Pick. Pinter, London (1989), ISBN 0–86187–763–2, £36.00     

A mathematical programming approach to the scheduling of sorting operations

In this paper we describe an approach to the scheduling and/or real-time control of sorting operations in the presence of deadlines. The problem arises in the postal service where mail has to be sorted by zip codes, and in the banking system where checks have to be sorted according to the bank on which they are drawn. In both applications losses are incurred if items miss their clearing deadlines. For example, in check-sorting an extremely important objective of the control system is to reduce the “float” i.e., the total dollar value of the checks which miss their deadlines. The proposed real-time control system utilizes a linear program which chooses between alternative sort-patterns and assigns the various processing steps to the time periods between deadlines.     

Discrete stochastic optimization using variants of the stochastic ruler method

We present two random search methods for solving discrete stochastic optimization problems. Both of these methods are variants of the stochastic ruler algorithm. They differ from our earlier modification of the stochastic ruler algorithm in that they use different approaches for estimating the optimal solution. Our new methods are guaranteed to converge almost surely to the set of global optimal solutions under mild conditions. We discuss under what conditions these new methods are expected to converge faster than the modified stochastic ruler algorithm. We also discuss how these methods can be used for solving discrete optimization problems when the values of the objective function are estimated using either transient or steady‐state simulation. Finally, we present numerical results that compare the performance of our new methods with that of the modified stochastic ruler algorithm when applied to solve buffer allocation problems. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.