A linear programming approach to geometric programs

A cutting plane method, based on a geometric inequality, is described as a means of solving geometric programs. While the method is applied to the primal geometric program, it is shown to retain the geometric programming duality relationships. Several methods of generating the cutting planes are discussed and illustrated on some example problems.     

Computation techniques for large scale undiscounted markov decision processes

In this paper we consider computation techniques associated with the optimization of large scale Markov decision processes. Markov decision processes and the successive approximation procedure of White are described. Then a procedure for scaling continuous time and renewal processes so that they are amenable to the White procedure is discussed. The effect of the scale factor value on the convergence rate of the procedure and insights into proper scale factor selection are given.     

Queueing processes and trade-offs during ship-to-shore transfer of cargo

This article examines the ship-to-shore transfer of cargo from ships that are located offshore. In these situations, cargo is transferred from the ships to smaller craft, which in turn transport the cargo the remaining distance to shore. These craft cycle back and forth from the ship to the shore until the transfer is complete. Queueing of these craft often occurs, as they must wait at either the ship or the shore for a loading or unloading position to become free. Two different methods of modeling this ship-to-shore transfer of cargo are developed and applied. One is an analytic queueing model and the other is a more traditional simulation model. The analytic model is found to produce results quite similar to the simulation model. Examples are shown that use these models to analyze trade-offs between variables affecting the ship-to-shore transfer of cargo and the total time to transfer a given amount of cargo ashore. © 1994 John Wiley & Sons, Inc.     

Causal analysis of Australian economic growth and military expenditure: A note

Chowdhury (1991) applied Granger causality methods to military expenditure and economic growth series in 55 developing countries. This note applies a similar approach to Australia and finds no causal relationship between military expenditure and growth in either direction.     

Termination policies for a two-state stochastic process

The purpose of this paper is to investigate and optimize policies which can be used to terminate a two-state stochastic process with a random lifetime. Such a policy consists of a schedule of times at which termination attempts should be made. Conditions are given which reduce the difficulty of finding the optimal policy by eliminating constraints and some boundary points from consideration. Finally, a bound for the optimal policy is derived for a case where some restrictions are imposed on the model.     

Postoptimality analysis in integer programming by implicit enumeration: The mixed integer case

This paper develops a method for doing postoptimality analysis on the mixed integer programming problem. The proposed procedures form a natural adjunct to enumerative I.P. algorithms that are linear programming based, and they are designed, in effect, to capitalize on insights generated as the problem is initially solved to do subsequent analysis upon it. In particular, limited ranging analysis is possible on selected parameters, as is the efficient resolving of the problem following parameter changes.     

Balancing and optimizing a portfolio of R&D projects

A mathematical formulation of an optimization model designed to select projects for inclusion in an R&D portfolio, subject to a wide variety of constraints (e.g., capital, headcount, strategic intent, etc.), is presented. The model is similar to others that have previously appeared in the literature and is in the form of a mixed integer programming (MIP) problem known as the multidimensional knapsack problem. Exact solution of such problems is generally difficult, but can be accomplished in reasonable time using specialized algorithms. The main contribution of this paper is an examination of two important issues related to formulation of project selection models such as the one presented here. If partial funding and implementation of projects is allowed, the resulting formulation is a linear programming (LP) problem which can be solved quite easily. Several plausible assumptions about how partial funding impacts project value are presented. In general, our examples suggest that the problem might best be formulated as a nonlinear programming (NLP) problem, but that there is a need for further research to determine an appropriate expression for the value of a partially funded project. In light of that gap in the current body of knowledge and for practical reasons, the LP relaxation of this model is preferred. The LP relaxation can be implemented in a spreadsheet (even for relatively large problems) and gives reasonable results when applied to a test problem based on GM's R&D project selection process. There has been much discussion in the literature on the topic of assigning a quantitative measure of value to each project. Although many alternatives are suggested, no one way is universally accepted as the preferred way. There does seem to be general agreement that all of the proposed methods are subject to considerable uncertainty. A systematic way to examine the sensitivity of project selection decisions to variations in the measure of value is developed. It is shown that the solution for the illustrative problem is reasonably robust to rather large variations in the measure of value. We cannot, however, conclude that this would be the case in general. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 18–40, 2001     

Labor staffing and scheduling models for controlling service levels

The problems of labor staffing and scheduling have received substantial attention in the literature. We introduce two new models of the labor staffing and scheduling problems that avoid the limitations of existing models. Collectively, the models have five important attributes. First, both models ensure the delivery of a minimally acceptable level of service in all periods. Second, one model can identify the least expensive way of delivering a specified aggregate level of customer service (the labor staffing problem and a form of labor scheduling problem). Third, the other model can identify the highest level of service attainable with a fixed amount of labor (the other form of the labor scheduling problem). Fourth, the models enable managers to identify the pareto relationship between labor costs and customer service. Fifth, the models allow a degree of control over service levels that is unattainable with existing models. Because of these attributes, which existing models largely do not possess, we expect these models to have broad applicability in a wide range of organizations operating in both competitive and noncompetitive environments. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 719–740, 1997