Robust fluid control of multiclass queueing networks

Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2006.

Bibliographic Details
Main Author: Su, Hua, S.M. Massachusetts Institute of Technology
Other Authors: Dimitris J. Bertsimas.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2007
Subjects:
Online Access:http://hdl.handle.net/1721.1/39212
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author Su, Hua, S.M. Massachusetts Institute of Technology
author2 Dimitris J. Bertsimas.
author_facet Dimitris J. Bertsimas.
Su, Hua, S.M. Massachusetts Institute of Technology
author_sort Su, Hua, S.M. Massachusetts Institute of Technology
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description Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2006.
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spelling mit-1721.1/392122019-04-12T21:40:55Z Robust fluid control of multiclass queueing networks Robust fluid control of multiclass queuing networks Su, Hua, S.M. Massachusetts Institute of Technology Dimitris J. Bertsimas. Massachusetts Institute of Technology. Computation for Design and Optimization Program. Massachusetts Institute of Technology. Computation for Design and Optimization Program. Computation for Design and Optimization Program. Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2006. Includes bibliographical references (p. 89-92). This thesis applies recent advances in the field of robust optimization to the optimal control of multiclass queueing networks. We develop models that take into account the uncertainty of interarrival and service time in multiclass queueing network problems without assuming a specific probability distribution, while remaining highly tractable and providing insight into the corresponding optimal control policy. Our approach also allows us to adjust the level of robustness of the solution to trade off performance and protection against uncertainty. We apply robust optimization to both open and closed queueing networks. For open queueing networks, we study control problems that involve sequencing, routing and input control decision, and optimize the total holding cost. For closed queueing networks, we focus on the sequencing problem and optimize the throughput. We compare the robust solutions to those derived by fluid control, dynamic programming and stochastic input control. We show that the robust control policy leads to better performance. Robust optimization emerges as a promising methodology to address a wide range of multiclass queueing networks subject to uncertainty, as it leads to representations of randomness that make few assumptions on the underlying probabilities. It also remains numerically tractable, and provides theoretical insights into the structure of the optimal control policy. by Hua Su. S.M. 2007-10-19T20:31:51Z 2007-10-19T20:31:51Z 2006 2006 Thesis http://hdl.handle.net/1721.1/39212 85843832 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 92 p. application/pdf Massachusetts Institute of Technology
spellingShingle Computation for Design and Optimization Program.
Su, Hua, S.M. Massachusetts Institute of Technology
Robust fluid control of multiclass queueing networks
title Robust fluid control of multiclass queueing networks
title_full Robust fluid control of multiclass queueing networks
title_fullStr Robust fluid control of multiclass queueing networks
title_full_unstemmed Robust fluid control of multiclass queueing networks
title_short Robust fluid control of multiclass queueing networks
title_sort robust fluid control of multiclass queueing networks
topic Computation for Design and Optimization Program.
url http://hdl.handle.net/1721.1/39212
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