Past Awards
The 2004 John von Neumann Theory Prize is awarded to J. Michael Harrison for his profound contributions to two major areas of operations research and management science: stochastic networks and mathematical finance.
Over the past 30 years, Harrison has spearheaded the formulation, development and application of the theory of Brownian networks for performance analysis and control of stochastic processing networks. He has defined a framework with elegance and depth, communicating clearly its purpose and outstanding issues, and with Stanford students and co-authors has repeatedly demonstrated its success in structuring and addressing a range of important questions that arise in application areas as diverse as manufacturing and telecommunications. Under his intellectual leadership, heavy traffic theory has gone from being an esoteric pursuit practiced by a small band of devotees to being a powerful and widely accepted technique, used by many researchers in the applied probability/queueing community.
In a pair of papers co-authored respectively with David Kreps and Stanley Pliska, Harrison showed that a price process is arbitrage free if and only if it is, when appropriately renormalized, a martingale for some equivalent probability measure. The careful definition and structuring of the general framework has stood the test of time: most of the theory of financial asset pricing in a dynamic setting is based squarely on the machinery laid down by Harrison and his collaborators. This literature numbers literally in the thousands of research papers. The equivalent martingale measure is also now a standard starting point for the analysis of optimal portfolio choice, a subject almost as large. It is difficult to overstate the impact that this work has had, ranging from the most abstract theory of stochastic processes to the day-to-day functioning of the financial industry.
The Lanchester prize for 2001 is awarded to J. Michael Harrison for a series of papers in performance analysis and control of Brownian networks.
- Brownian Models of Open Processing Networks: Canonical Representation of Workload, Annals of Applied Probability, Vol. 10 (2000), 75-103.
- Dynamic Control of Brownian Networks: State Space Collapse and Equivalent Workload Formulations, with J. A. Van Mieghem, Annals of Applied Probability, Vol. 7 (1997), 747-771.
- The BIGSTEP Approach to flow management in stochastic processing networks, in F.P. Kelly. I. Ziedins, and S. Zachary (eds.), Stochastic Networks: Theory and Applications, 57-90, Oxford University press, 1996.
- Brownian Models of Queueing Networks with Heterogeneous Customer Populations, in W. Fleming and P.-L. Lions (eds.), Stochastic Differential Systems, Stochastic Control Theory and Applications, IMA Volumes in Mathematics and its Applications, Volume 10, 147-186, Springer-Verlag, New York, 1988.
These papers, which are part of Professor Harrison's ongoing investigation of the properties of stochastic networks, propose a theory of performance analysis and control of multi-class Brownian networks. This work includes many of the strongest results known to date about Brownian networks. The work is both highly original and very clearly presented. It has had a substantial impact on the fields of applied probability and operations research. Professor Harrison's research program in this area has also produced and attracted some of the leading researchers in our field.
—Presented by: Dimitris Bertsimas, Lanchester Prize Committee Chair