Naval Research Logistics announces Kuhn Prize winner

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  • Author: Statistics Views
  • Date: 17 November 2016
  • Copyright: Image appears courtesy of Princeton University

Each year, the journal Naval Research Logistics awards the Kuhn Prize to the best paper published over the past three years. The purpose of the award is to recognize and reward outstanding research published in the Journal.

This year, the award goes to 'Maintenance scheduling for modular systems: Modeling and algorithms' by Retsef Levi, Thomas Magnanti, Jack Muckstadt, Danny Segev and Eric Zarybnisky, which was published in Volume 61, Issue 6
September 2014, pages 472–488.

thumbnail image: Naval Research Logistics announces Kuhn Prize winner

The award is named after the late Harold W. Kuhn, Professor Emeritus of Mathematics at Princeton University who won the 1980 John von Neumann Theory Prize along with David Gale and Albert W. Tucker. He is best known for the Karush–Kuhn–Tucker conditions and his contributions to the theory of games.

The prize consists of a certificate and a monetary award. Papers are selected by members of the Journal’s Editorial Board and a final committee decides on the winner.

Commenting on their choice of winner, Prize Committee members Damian Beil and Michal Tzur said, 'The authors study a problem in which scheduled maintenance need to be determined for modular systems, consisting of multiple components. Each component has a respective cycle limit, which specifies the time interval in which this component must be repaired or replaced. The goal is to compute a cost minimizing feasible maintenance schedule.

The authors use a general way to model the work of maintaining a set of components, which is described through a dependency tree structure. Using this structure they show that the cost of performing maintenance work on a set of components is submodular, which make the resulting models computationally challenging. Due to the generality of this formulation, the authors can model a variety of settings arising in maintaining modular systems, for example, those that arise in Air Force aircraft maintenance.

The general formulation of this practical problem is addressed by a mathematically rigorous and elegant analysis. In particular, based on their lower bound development, two simple-to-implement heuristic algorithms were shown to provide a constant worst case ratio. An extensive computational study, inspired by practical settings at the Air Force, demonstrates that these algorithms perform very well empirically.

The analysis connects two seemingly disparate areas of research, namely, maintenance and inventory management. They authors make a powerful analogy between the structure of these two problem domains and leverage ideas from inventory models to help solve maintenance scheduling problems.

Finally, the paper itself is written in a concise and accessible fashion. It addresses a very relevant yet challenging problem, and through an elegant analysis arrives at powerful and practical results. For the above reasons we find it deserving special recognition and recommend it to be the recipient of the 2016 Kuhn Award.'

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