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-
- Description:
- This dissertation presents novel advancements in the field of continuous nonlinear optimization, focusing on the development of efficient second-order methods for second-order conic programs (SOCPs) and continuous nonlinear two-stage optimization problems. The primary focus is on the theory and computations of Sequential Quadratic Programming (SQP) methods, which are widely used...
- Keyword:
- Nonlinear Optimization, Second-order Cone Programs, Two-stage Optimization, and Sequential Quadratic Programming
- Subject:
- Industrial engineering and Operations research
- Creator:
- Luo, Xinyi
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 08/23/2023
- Date Created:
- 2023-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_1013576 and http://dissertations.umi.com/northwestern:16752
-
- Description:
- Recommender systems (RSs) have become essential tools that provide personalized recommendations to their users. These systems may consider user, item provider, and system requirements simultaneously. With the inclusion of possibly clashing considerations, there is a growing focus on solving multiple-objective recommender system (MORS) problems as efficiently as possible. The constrained...
- Keyword:
- Constrained optimization, Recommender systems, and Personal recommendations
- Subject:
- Industrial engineering
- Creator:
- Seymen, Sinan
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 05/31/2023
- Date Created:
- 2023-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_975783 and http://dissertations.umi.com/northwestern:16462
-
- Description:
- In reinforcement learning (RL), an agent aims to learn the optimal policy by interacting with the environment and collecting the reward for each action taken. With the aid of strong function approximators such as the neural networks, RL achieves tremendous empirical successes in various scenarios, including game playing \citep{silver2016mastering, silver2017mastering},...
- Subject:
- Industrial engineering
- Creator:
- Wang, Lingxiao
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 09/22/2022
- Date Created:
- 2022-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:16246 and etdadmin_upload_928403
-
- Description:
- While deep reinforcement learning achieves tremendous successes in practice, its efficiencies are rarely understood in theory. The dissertation contains three parts, with each part corresponding to the study of an independent theoretical reinforcement learning problem. The three parts in all discuss the mechanism of how (deep) reinforcement learning efficiently solves...
- Subject:
- Industrial engineering
- Creator:
- Cai, Qi
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 09/22/2022
- Date Created:
- 2022-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_928893 and http://dissertations.umi.com/northwestern:16255
-
- Description:
- This thesis develops novel methods for generating space-filling designs inside a designspace and subsampling from a data set. It incorporates materials from two papers by the author: Shang and Apley 2021; Shang, Apley, and Mehrotra 2022a. Chapter 1 discusses space-filling designs of computer experiments, which is publishedas Shang and Apley...
- Keyword:
- fully-sequential, diversity subsampling, design of computer experiments, space-filling, and custom subsampling
- Subject:
- Industrial engineering and Statistics
- Creator:
- Shang, Boyang
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 09/22/2022
- Date Created:
- 2022-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_919274 and http://dissertations.umi.com/northwestern:16168
-
- Description:
- In this dissertation, we aim to develop algorithms that achieve optimality with provable complexity guarantees under various settings in reinforcement learning (RL). Specifically, in Markov decision processes (MDPs), we study single-agent and multi-agent online RL, respectively, and offline RL under the presence of unobserved confounders. Single-agent online RL. We design...
- Subject:
- Industrial engineering and Computer science
- Creator:
- Fu, Zuyue
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 09/22/2022
- Date Created:
- 2022-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_927346 and http://dissertations.umi.com/northwestern:16223
-
- Description:
- In this dissertation, we aim to develop efficient algorithms with theoretical guarantees for several data-driven decision making problems. Specifically, we study the data-driven deci- sion making from three different perspectives: statistical learning, nonconvex optimization, and control of stochastic system. This dissertation contains three parts. In the first part, we study...
- Subject:
- Industrial engineering
- Creator:
- Chen, Yi
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/02/2022
- Date Created:
- 2021-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_863393 and http://dissertations.umi.com/northwestern:15869
-
- Description:
- In this thesis, we aim to develop efficient algorithms with theoretical guarantees for noisy nonlinear optimization problems, with and without constraints, under various different assumptions. Apart from Chapter 1 which provides relevant backgrounds, the remaining of thesis is divided into four chapters. In Chapter 2, we establish the theoretical convergence...
- Keyword:
- LBFGS, BFGS, noisy optimization, nonlinear optimization, quasi-Newton, and derivative-free optimization
- Subject:
- Industrial engineering and Computer science
- Creator:
- Xie, Yuchen
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 10/07/2021
- Date Created:
- 2021-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_844865 and http://dissertations.umi.com/northwestern:15749
-
- Description:
- Massive amounts of data with a large number of predictors routinely arrive in data systems as a result of recent developments in data collection technology. In this data-intensive world, predictive models are more important than ever to extract information and make decisions, and are widely applied in many different fields....
- Subject:
- Industrial engineering
- Creator:
- Surer, Ozge
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/01/2021
- Date Created:
- 2020-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_773016 and http://dissertations.umi.com/northwestern:15344
-
- Description:
- Multistage optimization is a prominent modeling tool to solve a broad range of dynamic decision-making problems in the presence of uncertainty. However, computing optimal policies is intractable, since they are obtained by considering all possible realizations of uncertainties and subsequent future decisions over time. To overcome these challenges, we present...
- Keyword:
- Robust Optimization, Multistage Optimization, Dynamic Policies, Distributionally Robust Optimization, and Adaptive Policies
- Subject:
- Industrial engineering and Operations research
- Creator:
- Han, Eojin
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/01/2021
- Date Created:
- 2020-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:15200 and etdadmin_upload_756991
-
- Description:
- Constrained optimization problems are prevalent in all areas of science and engineering, and many well-known numerical methods have been developed to solve these problems. Yet, when there exists random quantities in the model under consideration, most of the deterministic methods are no longer effective. In this dissertation, we address parameter...
- Keyword:
- chance constraints, optimal power flow, nonlinear programming, and stochastic programming
- Subject:
- Industrial engineering
- Creator:
- Pena-Ordieres, Alejandra
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/01/2021
- Date Created:
- 2020-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:15173 and etdadmin_upload_752377
-
- Description:
- Optimization via simulation (OvS) is the practice of minimizing or maximizing the expected value of the output of a stochastic simulation model with respect to controllable decision variables. Stochastic simulation is a standard tool within operations research and is often required to model complex systems subject to uncertainty where it...
- Keyword:
- Optimization via Simulation, Optimization, and Stochastic Simulation
- Subject:
- Industrial engineering and Operations research
- Creator:
- Semelhago, Mark
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/01/2021
- Date Created:
- 2020-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:15377 and etdadmin_upload_779793
-
- Description:
- In machine learning, classification that assigns a label to a sample is a fundamental problem and serves a building block for various applications of artificial intelligence such as speech recognition, sentimental analysis, and image recognition. During the last years, deep learning rejuvenates artificial intelligence; in particular, it leads to tremendous...
- Keyword:
- Classification, Deep learning, and Machine learning
- Subject:
- Industrial engineering
- Creator:
- Koo, Jaehoon
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 01/21/2021
- Date Created:
- 2020-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:15036 and etdadmin_upload_729998
-
- Description:
- In this dissertation, we study models and methods to address uncertainties that can vary in optimization problems. Robust optimization is a popular approach for optimization under uncertainty, especially if limited information is available about the distribution of the uncertainty. It models the uncertainty through sets and finds a robust optimal...
- Keyword:
- variable uncertainty, optimization, decision dependent uncertainty, and robust optimization
- Subject:
- Industrial engineering and Operations research
- Creator:
- Sharma, Kartikey
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 04/29/2020
- Date Created:
- 2020-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_718511 and http://dissertations.umi.com/northwestern:14998
-
- Description:
- The goal of this thesis is to design practical algorithms for nonlinear optimization in the case where the objective function is deterministic or stochastic. Problems of this nature arise in many applications including machine learning and image processing. The thesis is divided into four main chapters. Chapters \ref{chap:Inexact}, \ref{chap:Adasample} and...
- Subject:
- Industrial engineering and Operations research
- Creator:
- Bollapragada, Vijaya Raghavendra
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/12/2020
- Date Created:
- 2019-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:14659 and etdadmin_upload_662754
-
- Description:
- This dissertation develops a new framework and algorithms for statistical process control of stochastic textured surface data that have no distinct features other than stochastic characteristics that vary randomly (e.g., image data of textiles or material microstructures and surface metrology data of metal parts). All methods are general and nonparametric...
- Keyword:
- Industrial Statistics, Anomaly Detection, Defect Detection, Supervised Learning, Quality Engineering, and Image Dissimilarity
- Subject:
- Industrial engineering
- Creator:
- Bui, Anh Tuan
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/12/2020
- Date Created:
- 2019-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_680004 and http://dissertations.umi.com/northwestern:14772
-
- Description:
- Cancer radiation therapy relies on optimized treatment plans whose quality assessment is judged by dosimetric planning aims. It is computationally prohibitive to incorporate the planning aims into the optimization models. Therefore, there exists a disconnect between the two steps of (1) optimizing a plan and (2) evaluating the optimized plan,...
- Keyword:
- Planning Aims, Robust Optimization, Data Driven, Radiation Therapy, and Knowledge Driven
- Subject:
- Industrial engineering and Operations research
- Creator:
- Shojaei, Sayyedeh Nastaran
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/12/2020
- Date Created:
- 2019-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:14806 and etdadmin_upload_685183
-
- Description:
- The vast majority of interactions between customers and service providers are experiences that extend over time. Service systems that deliver excellent customer experience achieve greater customer satisfaction and therefore customer loyalty, and eventually raise revenue. The temporal aspects of service delivery have not yet been analyzed as carefully as its...
- Keyword:
- Predictive Analytics, Service Operations, Satisfaction, Wait-time, and Markov Decision Process
- Subject:
- Industrial engineering and Operations research
- Creator:
- Ansari, Sina
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/12/2020
- Date Created:
- 2018-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_617413 and http://dissertations.umi.com/northwestern:14402
-
- Description:
- Computer simulation experiments are commonly used as an inexpensive alternative to real-world experiments to form a metamodel that approximates the input-output relationship of the real-world experiment. The metamodel can be useful for decision making and making predictions for inputs that have not been evaluated yet since it can be evaluated...
- Keyword:
- Metamodel, Gaussian process, Composite grid design, Sequential computer experiment, and Computer experiment
- Subject:
- Industrial engineering and Statistics
- Creator:
- Erickson, Collin
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/12/2020
- Date Created:
- 2019-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:14683 and etdadmin_upload_663282