Robustness of efficient server assignment policies to service time distributions in finite‐buffered lines

We study the assignment of flexible servers to stations in tandem lines with service times that are not necessarily exponentially distributed. Our goal is to achieve optimal or near‐optimal throughput. For systems with infinite buffers, it is already known that the effective assignment of flexible servers is robust to the service time distributions. We provide analytical results for small systems and numerical results for larger systems that support the same conclusion for tandem lines with finite buffers. In the process, we propose server assignment heuristics that perform well for systems with different service time distributions. Our research suggests that policies known to be optimal or near‐optimal for Markovian systems are also likely to be effective when used to assign servers to tasks in non‐Markovian systems. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

The multiplicative representation for multiple objectives optimization with an application for arms procurement

Multiple Objectives Optimization is much seen in combination with linear functions and even with linear programming, together with an adding of the objectives by using weights. With distance functions, normalization instead of weights is used. It is also possible that together with an additive direct influence of the objectives on the utility function a mutual utility of the objectives exists under the form of a multiplicative representation. A critical comment is brought on some representations of this kind. A full‐multiplicative form may offer other opportunities, which will be discussed at length in an effort to exclude weights and normalization. This theoretical approach is followed by an application for arms procurement. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 327–340, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10014     

Analysis of an Alternative Military Healthcare Benefit Design

Abstract

The Military Compensation and Retirement Modernization Commission was established by the Congress in 2013 to perform a systematic review of military compensation to address rising costs and other trends. Their recommendation for reforming the TRICARE health care program was sweeping, and differed greatly from earlier proposals that focused on increasing beneficiary cost shares. Specifically, the commission proposed overhauling the current benefit delivery model and replacing it with a premium-based insurance model offering a menu of DoD-sponsored private health plans. The analysis presented here is based on work that supported the commission by estimating the budgetary impact of its proposed reforms. Results indicate that movement towards the premium-based model would produce an annual budgetary cost savings in the $2 billion to $4 billion range, with a best savings estimate of $3.2 billion.     

An algorithm for the solution of a location problem with metric constraints

In many location problems, the solution is constrained to lie within a closed set. In this paper, optimal solutions to a special type of constrained location problem are characterized. In particular, the location problem with the solution constrained to be within a maximum distance of each demand point is considered, and an algorithm for its solution is developed and discussed.     

Generalized programming by linear approximation of the dual gradient: Equality constraints

A modified generalized programming procedure is presented for solving concave programming problems with equality constraints. The procedure constructs convenient linear approximations of the gradient of the dual and finds points where the approximating functions vanish. In the quadratic programming case, the procedure is finitely convergent. Global convergence is established for the non-quadratic case. Illustrative numerical examples are included.     

Optimal location of a single service center of certain types

Hakimi has considered the problem of finding an optimal location for a single service center, such as a hospital or a police station. He used a graph theoretic model to represent the region being serviced. The communities are represented by the nodes while the road network is represented by the ares of the graph. In his work, the objective is one of minimizing the maximum of the shortest distances between the vertices and the service center. In the present work, the region being serviced is represented by a convex polygon and communities are spread over the entire region. The objective is to minimize the maximum of Euclidian distances between the service center and any point in the polygon. Two methods of solution presented are (i) a geometric method, and (ii) a quadratic programming formulation. Of these, the geometric method is simpler and more efficient. It is seen that for a class of problems, the geometric method is well suited and very efficient while the graph theoretic method, in general, will give only approximate solutions in spite of the increased efforts involved. But, for a different class of problems, the graph theoretic approach will be more appropriate while the geometric method will provide only approximate solutions though with ease. Finally, some feasible applications of importance are outlined and a few meaningful extensions are indicated.     

Explicit solution of partitioning problems over a 1‐dimensional parameter space

We consider a class of partitioning problems where the partitioned set is a finite set of real numbers and the objective function of a partition is a function of the vector whose coordinates are the sums of the elements in each part of the given partition (the number of such parts is assumed given). We obtain an explicit solution of such partitioning problem with polynomial complexity bounds. © John Wiley & Sons, Inc. Naval Research Logistics 47: 531–540, 2000     

Optimal scheduling of reader—systems

We consider a reader—writer system consisting of a single server and a fixed number of jobs (or customers) belonging to two classes. Class one jobs are called readers and any number of them can be processed simultaneously. Class two jobs are called writers and they have to be processed one at a time. When a writer is being processed no other writer or readers can be processed. A fixed number of readers and writers are ready for processing at time 0. Their processing times are independent random variables. Each reader and writer has a fixed waiting cost rate. We find optimal scheduling rules that minimize the expected total waiting cost (expected total weighted flowtime). We consider both nonpreemptive and preemptive scheduling. The optimal nonpreemptive schedule is derived by a variation of the usual interchange argument, while the optimal schedule in the preemptive case is given by a Gittins index policy. These index policies continue to be optimal for systems in which new writers enter the system in a Poisson fashion. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 483–495, 1998