An interactive approach to multicriteria sorting for quasiconcave value functions

In this article, we develop an interactive algorithm to place alternatives in ordered preference classes for a decision maker (DM) with an increasing quasiconcave value function. Such value functions are quite general in that they include linear and concave value functions. Our aim is to elicit sorting information from the DM as few times as possible; our algorithm places other alternatives using previous responses from the DM utilizing properties of quasiconcave value functions. As an application, we sort 81 global MBA programs into preference classes using criteria such as alumni career progress, idea generation, and diversity. We study the performance of our proposed algorithm, when we change the number of criteria, number of alternatives, and introduce response errors. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 447–457, 2014     

Index policies for the routing of background jobs

Arriving (generic) jobs may be processed at one of several service stations, but only when no other (dedicated) jobs are waiting there. We consider the problem of how to route these incoming background jobs to make best use of the spare service capacity available at the stations. We develop an approximative approach to Whittle's proposal for restless bandits to obtain an index policy for routing. The indices concerned are increasing and nonlinear in the station workload. A numerical study testifies to the strong performance of the index policies developed. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Higher‐order Markov chain models for categorical data sequences*

In this paper we study higher‐order Markov chain models for analyzing categorical data sequences. We propose an efficient estimation method for the model parameters. Data sequences such as DNA and sales demand are used to illustrate the predicting power of our proposed models. In particular, we apply the developed higher‐order Markov chain model to the server logs data. The objective here is to model the users' behavior in accessing information and to predict their behavior in the future. Our tests are based on a realistic web log and our model shows an improvement in prediction. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Strategies for managing the flexible capacity in the airline industry

The ability to effectively match supply and demand under uncertainty can result in significant revenue benefits in the airline industry. We study the benefits of a Demand Driven Swapping (DDS) approach that takes advantage of the flexibilities in the system and dynamically swaps aircraft as departures near and more accurate demand information is obtained. We analyze the effectiveness of different DDS strategies, characterized by their frequency (how often the swapping decision is revised), in hedging against demand uncertainty. Swapping aircraft several weeks prior to departures will not cause much disturbance to revenue management and operations, but will be based on highly uncertain demands. On the other hand, revising the swapping decision later will decrease the possibility of bad swaps, but at a higher cost of disrupting airport services and operations. Our objective is to provide guidelines on how the flexible (swappable) capacity should be managed in the system. We study analytical models to gain insights into the critical parameters that affect the revenue benefits of the different swapping strategies. Our study determines the conditions under which each of the different DDS strategies is effective. We complement our analysis by testing the proposed DDS strategies on a set of flight legs, using data obtained from United Airlines. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

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.     

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     

Attrition through a partially coordinated area defense

An area defense consists of several groups that act independently, i.e., do not communicate with each other. Each group has a fixed number of defenders and a controller that allocates these defenders optimally against the individual attackers comprising an attack. We analyze the effectiveness of this partially coordinated defense against a simultaneous attack of known size in which all attackers are considered to be equally lethal. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2005.