INFORMS News: Stochastic Systems: The newest INFORMS journal

Editor-in-chief introduces Stochastic Systems and explains why you should consider publishing your work there.

By Shane Henderson

After more than six years being published through a cooperative agreement between the INFORMS Applied Probability Society and the Institute of Mathematical Statistics, Stochastic Systems is becoming an INFORMS journal. The first issue published under the INFORMS banner will come out later this year.

Stochastic Systems is the flagship journal of the INFORMS Applied Probability Society. It seeks to publish high-quality papers that substantively contribute to the modeling, analysis and control of stochastic systems. A paper’s contribution may lie in the formulation of new mathematical models, in the development of new mathematical or computational methods, in the innovative application of existing methods, or in the opening of new application domains.

Relative to application-focused journals, Stochastic Systems publishes papers in which applied probability plays a significant, not just supporting, role. Relative to other applied probability outlets, Stochastic Systems focuses exclusively on operations research content. As Stochastic Systems transitions to the INFORMS umbrella, my hope is that the content will broaden considerably beyond queueing theory, which has represented the majority of the work published there to date. While queueing theory remains an important part of the work relevant to Stochastic Systems and we are delighted to receive high-quality submissions in that sphere, there are many other exciting developments in the theory and applications of applied probability in operations research that are also relevant. For example, papers that explore the ties between applied probability and optimization, or with machine learning, or with game theory are relevant. (These are just a few examples.) We are also interested in papers in many application areas, including, but not limited to, service operations, healthcare, logistics and transportation, communications networks (including the Internet), computer systems, finance and risk management, manufacturing operations and supply chains, market and mechanism design, revenue management and pricing, the sharing economy, social networks and cloud computing. The editorial board provides direct evidence of our breadth of interests, and if you don’t see someone in an area that covers your paper, then why not contact me anyway? I’ll provide you with a quick decision about the relevance of your paper to the journal.

Why should you publish your work in Stochastic Systems?

  1. All papers published in Stochastic Systems are open access, and this will continue to be the case under the INFORMS banner. Moreover, there are no submission fees or page charges. You can submit your papers at Published papers are available at Once the transition to INFORMS is complete, the journal home will be – stay tuned!
  2. Stochastic Systems publishes work of broad interest to the operations research community. Papers that might otherwise go to, e.g., Management Science or Manufacturing & Service Operations Management might be relevant for Stochastic Systems if they include a significant applied probability component, and the applied probability need not be relegated to an appendix.
  3. Stochastic Systems aims to return reviews to authors within three months of submission and to publish articles online within two months of acceptance. I can assure you that I am proactive in keeping to this timetable. Starting in 2018, issues will appear quarterly.
  4. Stochastic Systems aims to publish a broad variety of operations research content, as evidenced by the partial list of relevant applications mentioned above. Indeed, one of our goals in publishing the journal is to strengthen the ties between the Applied Probability Society and the other communities of INFORMS.
  5. Stochastic Systems is publishing, and will continue to publish, work of the highest quality. This quality is in evidence in its editorial board, which includes five Fellows of INFORMS (Jim Dai, Paul Glasserman, Peter Glynn, John Tsitsiklis and Ruth Williams), three Fellows of the IMS (Dai, Glynn and Williams), three Fellows of the IEEE (Bruce Hajek, R. Srikant and Tsitsiklis) and four members of the National Academy of Engineering (Glynn, Hajek, Frank Kelly and Tsitsiklis). See for the full editorial board.

Some Example Papers

In order to buttress my earlier point about the breadth of research published in Stochastic Systems, I selected a few papers that emphasize this aspect of Stochastic Systems (and for this reason only). I do not give full references because the papers are easily found from the website above.

  • d’Aspremont, A., 2011, “Subsampling algorithms for semidefinite programming”
  • Tsitsiklis, J.N. and K. Xu, 2012, “On the power of (even a little) resource pooling.”
  • Wang, M. and D.P. Bertsekas, 2013, “On the convergence of simulation-based iterative methods for solving singular linear systems”
  • Juditsky, A. and Y. Nesterov, 2014, “Deterministic and stochastic primal-dual subgradient algorithms for uniformly convex minimization”
  • Armony, M., S. Israelit, A. Mandelbaum, Y. N. Marmor, Y. Tseytlin and G. B. Yom-Tov, 2015, “On patient flow in hospitals: A data-based queueing-science perspective”
  • Ata, B. and M. Akan, 2015, “On bid-price controls for network revenue management”
  • Braverman, A., J. G. Dai and J. Feng, 2016, “Stein’s method for steady-state diffusion approximations: An introduction through the Erlang-A and Erlang-C models”
  • Aldous, D., 2017, “Waves in a spatial queue”

I’m looking forward to receiving your submission.

Shane Henderson is the editor-in-chief of Stochastic Systems.