INFORMS Simulation Society's Lifetime Professional Achievement Award (2010), Operations Research Society of Israel's Lifetime Professional Award (2011)
Scientific career
Fields
Monte Carlo simulation, Applied probability, Stochastic modeling, Stochastic optimization
Institutions
University of Illinois Urbana-Champaign, Columbia University, Harvard University, Stanford University, IBM, Bell Laboratories
During his career, Rubinstein made fundamental and important contributions in these fields and advanced the theory and application of adaptive importance sampling, rare-event simulation, stochastic optimization, sensitivity analysis of simulation-based models, the splitting method, and counting problems concerning NP-complete problems.
He is well known as the founder of several breakthrough methods, such as
the score-function method, the stochastic counterpart method, and the cross-entropy method, which have numerous applications in combinatorial optimization and simulation.
In 2010 Prof. Rubinstein won the INFORMS Simulation Society's highest prize—the Lifetime Professional Achievement Award (LPAA), which recognizes scholars who have made fundamental contributions to the field of simulation that persist over most of a professional career.[7]
In 2011 Reuven Rubinstein won from the Operations Research Society of Israel (ORSIS) the Lifetime Professional Award (LPA), which recognizes scholars who have made fundamental contributions to the field of operations research over most of a professional career and constitutes ORSIS's highest award.[8]
Publications
Books
Rubinstein, R.Y., "Simulation and the Monte Carlo Method", Wiley, 1981.
Rubinstein, R.Y., "Monte Carlo Optimization, Simulation and Sensitivity of Queueing Networks", Wiley, 1986.
Rubinstein, R.Y., and A. Shapiro, "Discrete Event Systems: Sensitivity Analysis and Stochastic Optimization", Wiley, 1993.
Melamed, B., and R.Y. Rubinstein, "Modern Simulation and Modeling", Wiley, 1998.
Rubinstein, R.Y., and D.P. Kroese, "The Cross-Entropy Method: a Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation and Machine Learning", Springer, 2004.
Rubinstein, R.Y., and D.P. Kroese, "Simulation and the Monte Carlo Method", Second Edition, Wiley, 2008.
Rubinstein, R.Y., Rider, A., and R. Vaisman, "Fast Sequential Monte Carlo Methods for Counting and Optimization", Wiley, 2014.
Rubinstein, R.Y., and D.P. Kroese, "Simulation and the Monte Carlo Method", Third Edition, Wiley, 2017.
Journal articles
Rubinstein, R.Y., "The cross-entropy method for combinatorial and continuous optimization", Methodology and Computing in Applied Probability, 2, 127–190, 1999.
Rubinstein R.Y., "Randomized algorithms with splitting: Why the classic randomized algorithms do not work and how to make them work", Methodology and Computing in Applied Probability, 2009. doi:10.1007/s11009-009-9126-6
^ abcdRubinstein, Reuven Y.; Ridder, Ad; Vaisman, Radislav (2014). Fast Sequential Monte Carlo Methods for Counting and Optimization. Wiley. p. v. ISBN978-1-118-61226-2.