INFORMS Applied Probability Society

The Applied Probability Society is a subdivision of the Institute for Operations Research and the Management Sciences (INFORMS). The Society is concerned with the application of probability theory to systems that involve random phenomena, for example, manufacturing, communication network, computer network, service, and financial systems. The Society promotes the development and use of methods for the improvement of evaluation, control, and design of these systems. Such methods include (stochastic) dynamic programming, queueing theory, Markov decision process, discrete event dynamic systems, point processes, large deviations, reliability, and so on. Our members include practitioners, educators, and researchers with backgrounds in business, engineering, statistics, mathematics, economics, computer science, and other applied sciences.


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On patient flow in hospitals: A data-based queueing-science perspective Mor Armony, Shlomo Israelit, Avishai Mandelbaum, Yariv N. Marmor, Yulia Tseytlin, and Galit B. Yom-Tov Stochastic Systems, Volume 5, Number 1 (2015)
Moderate deviations for recursive stochastic algorithms Paul Dupuis and Dane Johnson Stochastic Systems, Volume 5, Number 1 (2015)
A linear response bandit problem Alexander Goldenshluger and Assaf Zeevi Stochastic Systems, Volume 3, Number 1 (2013)
Deterministic and stochastic primal-dual subgradient algorithms for uniformly convex minimization Anatoli Juditsky and Yuri Nesterov Stochastic Systems, Volume 4, Number 1 (2014)
Mean square convergence rates for maximum quasi-likelihood estimators Arnoud V. den Boer and Bert Zwart Stochastic Systems, Volume 4, Number 2 (2014)