Control of Fork-Join Processing Networks with Multiple Job Types and Parallel Shared Resources
Erhun Özkan, College of Administrative Sciences and Economics, Koç University


Networks in which the processing of jobs occurs both sequentially and in parallel are prevalent in many application domains, such as computer systems, healthcare, manufacturing, and project management. The parallel processing of jobs gives rise to synchronization constraints that can be a main reason for job delay. In comparison with feed-forward queueing networks that have only sequential processing of jobs, the approximation and control of networks that have synchronization constraints is less understood. One well-known modeling framework in which synchronization constraints are prominent is the fork-join processing network. Our objective is to find scheduling rules for fork-join processing networks with multiple job types and parallel shared resources. Jobs arriving in the system fork into arbitrary number of tasks, then those tasks are processed in parallel, and then they join and leave the network. There are shared resources processing multiple job types. We study the scheduling problem for those shared resources (that is, which type of job to prioritize at any given time) and propose an asymptotically optimal scheduling policy in diffusion scale.
The talk is based on the following papers:
• The manuscript in
• Özkan, E. and Ward, A. R. (2019) “On the control of Fork-Join Networks.” Mathematics of Operations Research, 44, 2, 532-564.

Short Bio

Erhun Özkan is an assistant professor in the College of Administrative Sciences and Economics, Koç University, Istanbul, Turkey. He received his BS and MS degrees in industrial engineering from Middle East Technical University. He obtained his Ph.D. from Data Sciences and Operations department of the Marshall School of Business, University of Southern California. His research interests include the applications of probability theory, queueing theory, and stochastic processes in matching markets, revenue management, inventory control, and healthcare systems.


Friday, March 6, 2020 at 4.00 pm in IE 03


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