Results 171 to 180 of about 3,492,516 (198)
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Stability and Continuity in Robust Optimization
SIAM Journal on Optimization, 2017Summary: We consider the stability of robust optimization (RO) problems with respect to perturbations in their uncertainty sets. In particular, we focus on robust linear optimization problems, including those with an infinite number of constraints, and consider uncertainty in both the cost function and constraints.
Timothy C. Y. Chan, Philip Allen Mar
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Almost Robust Discrete Optimization
European Journal of Operational Research, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Opher Baron +3 more
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Robust Optimization of Order Execution
IEEE Transactions on Signal Processing, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yiyong Feng +2 more
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Robustness of Robust Process Optimization
Quality Engineering, 2002[This abstract is based on the author's abstract.] Different strategies for robust process optimization have been used to solve the problem of unwanted variation in production processes, but a number of factors can influence the precision of the me..
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Relative Robust and Adaptive Optimization
INFORMS Journal on Computing, 2019Summary: Robust optimization has emerged in the operations research literature as a tractable and practical way to model uncertainty in optimization problems. Early approaches focused on relative worst-case objective functions, where the value of a solution is measured versus the best-possible solution over an uncertainty set of scenarios.
Dimitris Bertsimas, Iain Dunning
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Robustness of optimally robust controllers
[1991 Proceedings] The Twenty-Third Southeastern Symposium on System Theory, 2002The largest robust stability radius gamma (P/sub 0/) of a system P/sub 0/ is defined as the radius of the largest ball B/sub max/ in the gap metric centered at P/sub 0/ which can be stabilized by one single controller. Any controller which stabilizes B/sub max/ is called an optimally robust controller of P/sub 0/.
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2006
This thesis develops and explores the connections between risk theory and robust optimization. Specifically, we show that there is a one-to-one correspondence between a class of risk measures known as coherent risk measures and uncertainty sets in robust optimization.
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This thesis develops and explores the connections between risk theory and robust optimization. Specifically, we show that there is a one-to-one correspondence between a class of risk measures known as coherent risk measures and uncertainty sets in robust optimization.
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Distributionally Robust Stochastic Optimization with Wasserstein Distance
Mathematics of Operations Research, 2023Anton Kleywegt, Rui Gao
exaly