Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 165 for “"Robust optimization"”.
-
Robust optimization
We propose new methodologies in robust optimization that promise greater tractability, both theoretically and practically than the classical robust framework. We cover a broad range of mathematical optimization problems, including linear optimization (LP), quadratic constrained quadratic …
-
Nonconvex robust optimization
We propose a novel robust optimization technique, which is applicable to nonconvex and simulation-based problems. Robust optimization finds decisions with the best worst-case performance under uncertainty. If constraints are present, decisions should also be feasible under perturbations. In the …
-
Risk and robust optimization
… 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. An important consequence of this is that one may …
-
Stochastic analysis via robust optimization
… in the literature: stochastic analysis and optimization describing the uncertainty probabilistically and robust optimization describing the uncertainty deterministically. Instead, we propose a novel paradigm which leverages the conclusions of probability theory and the tractability of the …
-
Algorithms and concepts for robust optimization
In this work we consider uncertain optimization problems where no probability distribution is known. We introduce the approaches RecFeas and RecOpt to such a robust optimization problem, using a location theoretic point of view, and discuss both theoretical and algorithmic aspects. We then consider …
-
A robust optimization approach to finance
An important issue in real-world optimization problems is how to treat uncertain coefficients. Robust optimization is a modeling methodology that takes a deterministic view: the optimal solution is required to remain feasible for any realization of the uncertain coefficients within prescribed …
-
Advances in Nonconvex and Robust Optimization
Nonconvex optimization presents significant challenges, as identifying the global optimum is often difficult. This thesis introduces novel algorithms to find the exact solution of a broad class of nonconvex optimization problems. The thesis is structured into four parts. In Chapter 2, we propose a …
-
Robust Optimization and Groundwork for Problem Mapping
… instance of the problem. The algorithm was to be robust, as to be applicable to a wide array of problems without radical re-design per problem. This idea was fueled by the concept of Structure-Mapping Theory, where a set of knowledge is mapped from one domain to another based on the shared …
-
Robust optimization framework for wave energy converters
L'abstract è presente nell'allegato / the abstract is in the attachment
-
A robust optimization approach to online problems
In this thesis, we consider online optimization problems that are characterized by incrementally revealed input data and sequential irrevocable decisions that must be made without complete knowledge of the future. We employ a combination of mixed integer optimization (MIO) and robust optimization …
-
A robust optimization approach to network design
… program. To extend this formulation to discrete optimization problems, such as the link placement sub-problem, it is reformulated as a mixed integer linear program (MILP) by extending tools from robust optimization to Gaussian variables. Bounds are presented to relate capacity allocation to the …
-
Robust optimization, game theory, and variational inequalities
We propose a robust optimization approach to analyzing three distinct classes of problems related to the notion of equilibrium: the nominal variational inequality (VI) problem over a polyhedron, the finite game under payoff uncertainty, and the network design problem under demand uncertainty. In …
-
Global and Robust Optimization for Engineering Design
… improve conceptual design methods through better optimization, in order to address the challenge of designing future engineered systems. Aerospace design problems are tightly-coupled optimization problems, and require all-at-once solution methods for design consensus and global optimality. …
-
Advanced Ordered Weighted Averaging Methods in Robust Optimization
In decision-making under uncertainty, robust optimization is a critical tool across various fields, providing solutions that perform effectively across a range of scenarios where precise probabilities are unavailable or unreliable. Traditional approaches, such as min-max and min-max regret, focus …
-
Distributionally robust optimization with marginals : theory and applications
In this thesis, we consider distributionally robust optimization (DRO) problems in which the ambiguity sets are designed from marginal distribution information - more specifically, when the ambiguity set includes any distribution whose marginals are consistent with given prescribed distributions …
-
Robust optimization techniques and design of Li-ion batteries
This thesis applies robust optimization techniques to the design of Lithium-ion batteries with spatially varying porosities. The microstructure of a porous electrode was designed to minimize the Ohmic resistance. The spatial variation in the porosities was found to provide enhanced robustness of …
-
Distributionally robust optimization for design under partially observable uncertainty
… this challenge by formulating a distributionally robust design optimization problem, and presents computationally efficient algorithms for solving the problem. In distributionally robust optimization (DRO) methods, the designer acknowledges that they are unable to exactly specify a probability …
-
Tractable stochastic analysis in high dimensions via robust optimization
… such systems, probability theory, in contrast to optimization, has not been developed with computational tractability as an objective when the dimension increases. Correspondingly, some of its major areas of application remain unsolved when the underlying systems become multidimensional: Queueing …
-
Applications of robust optimization to queueing and inventory systems
This thesis investigates the application of robust optimization in the performance analysis of queueing and inventory systems. In the first part of the thesis, we propose a new approach for performance analysis of queueing systems based on robust optimization. We first derive explicit upper bounds …
-
Robust optimization for network-based resource allocation problems under uncertainty
… examines methods of proactive planning, that is, robust plan generation to protect against future uncertainty. By modeling uncertainties in data corresponding to service times, resource availability, supplies and demands, we can generate solutions that are more robust operationally, that is, more …
Page 1 of 9