Active Robust Optimization: Enhancing Robustness to Uncertain Environments

Many real world optimization problems involve uncertainties. A solution for such a problem is expected to be robust to these uncertainties. Commonly, robustness is attained by choosing the solution's parameters such that the solution's performance is less influenced by negative effects of...

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Bibliographic Details
Published in:	IEEE transactions on cybernetics Vol. 44; no. 11; pp. 2221 - 2231
Main Authors:	Salomon, Shaul, Avigad, Gideon, Fleming, Peter J., Purshouse, Robin C.
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.11.2014 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptation Adaptive design Algorithms Artificial Intelligence Brightness Computer Simulation Cybernetics Decision Support Techniques dynamic optimization Dynamic tests Ecosystem Equivalence evolutionary algorithms Expenses Feedback Linear programming Models, Statistical multiobjective optimization Nonlinear programming Optimization Pareto optimization Pattern Recognition, Automated - methods robust optimization Robustness Tables (data) Uncertainty Vectors multiobjective optimization Adaptive design dynamic optimization evolutionary algorithms robust optimization
ISSN:	2168-2267, 2168-2275, 2168-2275
Online Access:	Get full text
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