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What is Robust Optimization

Chapter 20
Handbook of Research on Next Generation Mobile Communication Systems
A field of optimization theory that deals with optimization problems in which a certain measure of robustness is sought against uncertainty that can be represented as deterministic variability in the value of the parameters of the problem itself and/or its solution.
Published in Chapter:
Advances in QoS/E Characterization and Prediction for Next Generation Mobile Communication Systems
Charalampos N. Pitas (National Technical University of Athens, Greece), Apostolos G. Fertis (SMA und Partner AG, Zurich, Switzerland), Dimitris E. Charilas (National Technical University of Athens, Greece), and Athanasios D. Panagopoulos (National Technical University of Athens, Greece)
Copyright: © 2016 |Pages: 24
DOI: 10.4018/978-1-4666-8732-5.ch020
Abstract
The scope of this work is to present a holistic approach in quality of service (QoS) and quality of experience (QoE) characterization and prediction in modern mobile communication networks. Analytically, multi radio access technologies have been deployed in order to deliver mobile services to quality demanded consumers. Quality of Experience (QoE) parameters describe the End-to-End (E2E) quality as experienced by the mobile users. These parameters are difficult to be measured and quantified. System Quality of Service (SQoS) parameters are metrics that are closely related to the network status, and defined from the viewpoint of the service provider rather than the service user. Moreover, E2E Service Quality of Service (ESQoS) parameters describe the QoS of the services and they are obtained directly from the QoE parameters by mapping them into parameters more relevant to network operators, service providers and mobile users. A useful technique for mobile network planning and optimization is to build reliable quality estimation models for mobile voice and video telephony service.
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More Results
Chapter 4
Multi-Objective Optimization of Two-Stage Thermo-Electric Cooler Using Differential Evolution: MO Optimization of TEC Using DE
Is a field of optimization theory that deals with optimization problems in which a certain measure of robustness is sought against uncertainty that can be represented as deterministic variability in the value of the parameters of the problem itself and/or its solution. There are a number of classification criteria for robust optimization problems/models. In particular, one can distinguish between problems dealing with local and global models of robustness; and between probabilistic and non-probabilistic models of robustness. Modern robust optimization deals primarily with non-probabilistic models of robustness that are worst case oriented and as such usually deploy Wald's maximum models.
Published in Chapter: Multi-Objective Optimization of Two-Stage Thermo-Electric Cooler Using Differential Evolution: MO Optimization of TEC Using DE; From: Handbook of Research on Computational Simulation and Modeling in Engineering
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