Operations Research, Systems Engineering and Industrial Engineering Commons^™

Essays In Robust Optimization With Applications To Finance And Renewable Energy, Hao Jiang

Operations Research and Engineering Management Theses and Dissertations

Real-world optimization problems are often sensitive to uncertainties caused by estimation errors, forecasting inaccuracy, and imprecise data information. These uncertainties bring significant challenges to decision-making in many areas. Robust optimization (RO) is a tool for addressing the challenges of parameter uncertainty. In this dissertation, we focus on the studies of RO on two problems. (1) In the study of finance, we proposed a tractable RO model for a Mean-Variance portfolio selection problem. We consider Markowitz's Mean-Variance Optimization when stock returns are modeled using Sharpe's single-index framework, but the model coefficients Alpha and Beta, are not precisely known. This study assumes …

Exact Models, Heuristics, And Supervised Learning Approaches For Vehicle Routing Problems, Zefeng Lyu

Doctoral Dissertations

This dissertation presents contributions to the field of vehicle routing problems by utilizing exact methods, heuristic approaches, and the integration of machine learning with traditional algorithms. The research is organized into three main chapters, each dedicated to a specific routing problem and a unique methodology. The first chapter addresses the Pickup and Delivery Problem with Transshipments and Time Windows, a variant that permits product transfers between vehicles to enhance logistics flexibility and reduce costs. To solve this problem, we propose an efficient mixed-integer linear programming model that has been shown to outperform existing ones. The second chapter discusses a practical …

Parameter Estimation For Patient Enrollment In Clinical Trials, Junyan Liu

Undergraduate Honors Theses

In this paper, we study the Poisson-gamma model for recruitment time in clinical trials. We proved several properties of this model that match our intuitions from a reliability perspective, did simulations on this model, and used different optimization methods to estimate the parameters. Although the behaviors of the optimization methods were unfavorable and unstable, we identified certain conditions and provided potential explanations for this phenomenon and further insights into the Poisson-gamma model.

Task Optimization Utilizing Digital Transformation Concepts - Automation Project Execution Via Agile Methodology, Anthony Steven Maiello

Theses and Dissertations

Task Optimization via the use of automated process improvements is becoming more widespread as more industries lean into the concepts surrounding digital transformation. This shift also necessitates a complementary adaptation in project management methodologies to support the rapid and ever-changing environment, requirements, and innovations. This thesis examines the effectiveness of Agile methodology in managing digital automation projects, with a specific focus placed on process improvements with systems engineering. It accomplished this by contrasting the original model, designed and derived utilizing traditional project management techniques, with the proposed model which is a direct result of the application of Agile project practices. …

Reliability Modeling And Improvement Of Critical Infrastructures: Theory, Simulation, And Computational Methods, José Carlos Hernández Azucena

Graduate Theses and Dissertations

This dissertation presents a framework for developing data-driven tools to model and improve the performance of Interconnected Critical Infrastructures (ICIs) in multiple contexts. The importance of ICIs for daily human activities and the large volumes of data in continuous generation in modern industries grant relevance to research efforts in this direction. Chapter 2 focuses on the impact of disruptions in Multimodal Transportation Networks, which I explored from an application perspective. The outlined research directions propose exploring the combination of simulation for decision-making with data-driven optimization paradigms to create tools that may provide stakeholders with optimal policies for a wide array …

Optimal Sequencing And Scheduling Algorithm For Traffic Flows Based On Extracted Control Actions Near The Airport, Sharmistha Chakrabarti

Electronic Theses and Dissertations, 2020-2023

This dissertation seeks to design an optimization algorithm, based on naturalistic flight data, with emphasis on safety to perform a benefits' analysis when sequencing and scheduling aircraft at the runway. The viability of creating a decision-support tool to aid air traffic controllers in sequencing and optimizing airport operations is evaluated through the benefits' analysis. Air traffic control is a complex and critical system that ensures the safe and efficient movement of aircraft within the airspace. This is particularly true in the immediate vicinity of an airport. Unlike in en-route or terminal area airspace where aircraft usually traverse well established routes …

Scheduling Problem With Drying Requirements, Machine Eligibility Restrictions, Setup Times, And Assembly Requirements For An Injection Molding Facility, Ashley Owens

Doctoral Dissertations

Previous research only focused on an unrelated parallel machine scheduling problem with setup and processing resources. However, some manufacturing environments, such as plastic injection molding, need different sequential and parallel processes before the facility can process jobs in the machines. For example, some raw materials are hygroscopic, and a dryer must remove moisture before being processed in the injection molding machine. These dryers are portrayed as parallel machines. The job rather than the machine determines the drying time. Once the drying stage is complete and the raw materials are transferred to the actual machines to run jobs, the scheduling problem …

Improving Mobility And Safety In Traditional And Intelligent Transportation Systems Using Computational And Mathematical Modeling, Shahrbanoo Rezaei

Doctoral Dissertations

In traditional transportation systems, park-and-ride (P&R) facilities have been introduced to mitigate the congestion problems and improve mobility. This study in the second chapter, develops a framework that integrates a demand model and an optimization model to study the optimal placement of P&R facilities. The results suggest that the optimal placement of P&R facilities has the potential to improve network performance, and reduce emission and vehicle kilometer traveled. In intelligent transportation systems, autonomous vehicles are expected to bring smart mobility to transportation systems, reduce traffic congestion, and improve safety of drivers and passengers by eliminating human errors. The safe operation …

Modeling And Solution Methodologies For Mixed-Model Sequencing In Automobile Industry, Ibrahim Ozan Yilmazlar

All Dissertations

The global competitive environment leads companies to consider how to produce high-quality products at a lower cost. Mixed-model assembly lines are often designed such that average station work satisfies the time allocated to each station, but some models with work-intensive options require more than the allocated time. Sequencing varying models in a mixed-model assembly line, mixed-model sequencing (MMS), is a short-term decision problem that has the objective of preventing line stoppage resulting from a station work overload. Accordingly, a good allocation of models is necessary to avoid work overload. The car sequencing problem (CSP) is a specific version of the …

Visibility Based Hospital Inpatient Unit Design., Uttam Karki

Electronic Theses and Dissertations

Patient fall is one of the adverse events in an inpatient unit of a hospital that can lead to disability and/or mortality. Healthcare literature suggests that increased visibility of patients by unit nurses is essential to improve patient monitoring and, in turn, reduce falls. However, such research has been descriptive in nature and does not provide an understanding of the characteristics of an optimal inpatient unit layout from a visibility-standpoint. This dissertation fills significant voids in this domain and adds much-needed realism to develop insights that hospital decision-makers can use to design their inpatient unit layout. Our first contribution (Chapter …

Resources Based Planning Framework For Infrastructure Maintenance And Rehabilitation Projects, Heba Gad

Theses and Dissertations

Infrastructure maintenance and rehabilitation projects involve activities scattered over a large geographical area (e.g., scattered road segments maintenance, telecom towers maintenance program, etc.). Planning such projects require a resource-based approach that accounts for the implications of resource mobility between activities’ locations in terms of time & cost. Existing scheduling techniques fall short of addressing the unique challenges of the scattered nature of these projects in combination with organization's limited resources availability. To address this need, this research presents a resources-based planning framework for infrastructure maintenance and rehabilitation scattered projects with the objective of enhancing resources utilization achieving time and cost …

Data-Driven Platform And Digital Operations, Bing Bai

Olin Business School Electronic Theses and Dissertations

The objective of this dissertation is to study the emerging operations issues on data-driven platforms and digital operations. With the increasing availability of data and the development of information technologies, platforms process a large amount of data in order to efficiently make daily operational decisions. Understanding human behaviors and the human-algorithm connection is instrumental to the success of this process. In my research, I implement field experiments and use structural models to study in-warehouse worker behavior and out-of-warehouse customer behavior in the last mile of logistics.

In Chapter 1, “The Impacts of Algorithmic Work Assignment on Fairness Perceptions and Productivity: …

Optimizing Wedding Venue Selection Process Using Integer Programming, Luis Rodriguez

Theses/Capstones/Creative Projects

Choosing the right wedding venue can be extremely difficult for the unsuspecting engaged couple. There is a myriad of variables that must be taken into account prior to the illustrious wedding date; these variables include the option for a reception, the location, and food requirements, to name a few. Consequently, the typical couple seems to spend multiple months researching and visiting many wedding spaces. However, even though months go into planning, it still is not a guarantee that all variables are accounted for. Furthermore, without a wedding planner, these couples may second-guess their chosen site due to seemingly arduous issues …

Efficient Routing For Disaster Scenarios In Uncertain Networks: A Computational Study Of Adaptive Algorithms For The Stochastic Canadian Traveler Problem With Multiple Agents And Destinations, Neel Chanchad

Graduate Theses and Dissertations

The primary objective of this research is to develop adaptive online algorithms for solving the Canadian Traveler Problem (CTP), which is a well-studied problem in the literature that has important applications in disaster scenarios. To this end, we propose two novel approaches, namely Maximum Likely Node (MLN) and Maximum Likely Path (MLP), to address the single-agent single-destination variant of the CTP. Our computational experiments demonstrate that the MLN and MLP algorithms together achieve new best-known solutions for 10,715 instances. In the context of disaster scenarios, the CTP can be extended to the multiple-agent multiple-destination variant, which we refer to as …

Electric Vehicle Routing Problem – Models And Algorithms, Hesamoddin Tahami

Engineering Management & Systems Engineering Theses & Dissertations

The transportation sector is a major greenhouse gas emitter that is heavily regulated to reduce its dependence on oil. These regulations along with the growing customer awareness of global warming have led to the investigation of new transportation problems that consider using eco-friendly vehicle fleets. Promising alternatives to traditional fleets include alternative fuel vehicles (AFVs) and electric vehicles (EVs). These twenty-first-century vehicles offer an appealing advantage of consistently reducing their environmental impact, but due to the current technology, they exhibit bothersome limitations. The short driving range along with limited charging infrastructure may consequently cause issues related to range anxiety, i.e., …

Urban Public Transportation Planning With Endogenous Passenger Demand, Yifei Sun

Dartmouth College Ph.D Dissertations

An effective and efficient public transportation system is crucial to people's mobility, economic production, and social activities. The Operations Research community has been studying transit system optimization for the past decades. With disruptions from the private sector, especially the parking operators, ride-sharing platforms, and micro-mobility services, new challenges and opportunities have emerged. This thesis contributes to investigating the interaction of the public transportation systems with significant private sector players considering endogenous passenger choice. To be more specific, this thesis aims to optimize public transportation systems considering the interaction with parking operators, competition and collaboration from ride-sharing platforms and micro-mobility platforms. …

Information System Availability Status And Its Impact On Customer Wait Times, Joshua A. Cramer

Theses and Dissertations

The Military Personnel Flight relies on Air Force Information Systems, specifically the Defense Enrollment Eligibility and Reporting System (DEERS), to manage the personnel records. When DEERS experiences a failure, then the operational ability of the Military Personnel Flight is affected. This study aims at identifying the impact Air Force information system’s availability status has on customer wait times using linear regression.

Simulating Autonomous Drone Swarm Behaviors In An Anti-Access Area Denial (A2ad) Environment, Alexander L. Martinez

Theses and Dissertations

Army senior military leaders are invested in acquiring modernized aerial platforms and equipment to augment the U.S. Army’s ability to overcome A2AD threats imposed by modern IADS. A prominent element of this modernization effort is the employment of autonomous drones to defeat IADS threats while minimizing risk to Army Soldiers. This research utilizes a framework for classifying the levels of autonomous capability along three dimensions: the ability to act alone, the ability to cooperate, and the ability to adapt. A virtual combat model, created using the AFSIM, simulates the engagement between an enemy IADS and a friendly formation comprised of …

Advancing Autonomous Swarm Behavior In A Simulated Anti-Access Area Denial (A2ad) Environment, Chad P. Macwilkinson

Theses and Dissertations

Advancements in modern IADS have bolstered A2AD environments and subsequently degraded the advantages that the Air Force once held, prompting a call to reform the nature of warfare in order to challenge these threats. A solution is weapon swarming technology, which has the ability to overwhelm IADS by engagement of a large numbers of low-cost, but lethal air assets that have autonomous functionalities. This research proposes the application of a four dimensional framework for autonomy to a swarm of cruise missiles. A virtual A2AD environment of two opposing forces is constructed using the AFSIM, wherein a manned bomber seeks to …

Inducing Sparsity Within High-Dimensional Remote Sensing Modalities For Lightning Prediction, Grace E. Metzgar

Theses and Dissertations

The uncertainty of lightning constantly threatens many weather-sensitive fields where the slightest presence of lightning can endanger valuable personnel and assets. The consequences of delaying operations have incited the research of methods that can accurately predict the location of future lightning strikes from the current weather conditions. High-dimensional remote sensing modalities contain information capable of detecting significant patterns and intensities within storms that could indicate the presence of lightning. This thesis induces sparsity into convolutional neural networks (CNNs) and remote sensing modalities through a combination of regularization and tensor decomposition techniques to call attention to sparse features that are most …

Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid

Theses and Dissertations

This research modeled and analyzed the effectiveness of different routing algorithms for penetration assets in an A2AD environment. AFSIM was used with different configurations of SAMs locations and numbers to compare the performance of AFSIM’s internal zone and shrink algorithm routers with a Dijkstra algorithm router. Route performance was analyzed through computational and operational metrics, including computational complexity, run-time, mission survivability, and simulation duration. This research also analyzed the impact of the penetration asset’s ingress altitude on those factors. Additionally, an excursion was conducted to analyze the Dijkstra algorithm router’s grid density holding altitude constant to understand its impact on …

Optimal Control Of Precision Airdrop Trajectories Using Direct Collocation And Analytical Methods, Edward J. Maxwell

Theses and Dissertations

The work herein investigates the preliminary designs of an optimal navigation controller for a scalable cylindrical airdrop system controlled with grid fins in planar motion. Precision airdrop capabilities are desired for a range of military and humanitarian missions. Fielded airdrop systems have not met desired performance objectives, particularly regarding accuracy. Direct collocation and analytical methods were utilized to solve the optimal control problem for the grid fin controlled precision airdrop system examined in this work. The optimal control problem was comprised of two phases: controlled descent and parachute descent. Minimum and maximum ranges for the system under varying wind fields …

The Aerial Refueling Asset Basing And Assignment Problem, Camryn E. Deames

Theses and Dissertations

With growing tensions in the European theatre and Indo-Pacific theatre, the constraints of aerial refueling impede the missions of Air Mobility Command and USTRANSCOM in their execution of both the National Security Strategy and National Defense Strategy. Introducing and integrating semi-autonomous aerial refueling aircraft is a logical next step due to advantages in endurance, survivability, runway requirements, and fuel offloading capacity. This research frames the Aerial Refueling Asset Basing and Assignment Problem with two model approaches: a baseline model and a fuel shuttle concept model. Whereas the former model considers instances with only manned refuelers or only semi-autonomous refuelers, the …

Probability Of Agreement As A Simulation Validation Methodology, Matthew C. Ledwith

Theses and Dissertations

Determining whether a simulation model is operationally valid requires the rigorous assessment of agreement between observed functional responses of the simulation model and the corresponding real world system or process of interest. This research seeks to extend and formulate the probability of agreement approach to the operational validation of simulation models. The first paper provides a methodological approach and an initial demonstration which leverages bootstrapping to overcome situations where one’s ability to collect real-world data is limited. The second paper extends the probability of agreement approach to account for second-order heteroscedastic variability structures and establishes a weighted probability of agreement …

Classification And Analysis Of Twitter Bot And Troll Accounts, Callan P. Mccormick

Theses and Dissertations

This research trains, tests, and analyzes bot and troll classification models using publicly available, open source datasets. Specifically, it applies decision tree, random forest, feed forward neural networks, and long-short term memory neural networks with hyperparameters tuned via designed experiment to five labeled bot datasets created between 2011 and 2020 and one dataset labeling state-sponsored disinformation accounts or trolls. The first three models utilize account profile features, while the last model applies natural language processing techniques, specifically GloVe embedding, to analyze a user’s Tweet history. Results indicate that the random forest model outperforms the other three models with an average …

Designing A Counter-Iads Drone Swarm: Using Evolution To Evaluate Combat Assumptions Underpinning Drone Swarm Target Assignment, Olin H. Kennedy

Theses and Dissertations

The original research goal was to combine the best techniques in the drone swarm literature and model a functional combat drone swarm that conducts a Suppression of Enemy Air Defense (SEAD) mission. However, the body of literature regarding Drone Swarm Target Assignment (DSTA) does not model enemy counteraction and assumes that the drones’ targets are compliant against destruction. Therefore, a model of enemy counteraction against drone swarms is developed, and Novel DSTA (NDSTA) is proposed to respond to the weaknesses of the current DSTA. Both methods of target assignment are combined with a tunable trajectory generation model, and the performance …

An Approximate Dynamic Programming Approach For Solving An Air Combat Maneuvering Problem With Directed Energy Weapons, Elisha A. Palm

Theses and Dissertations

Performing within visual range (WVR) air combat involves the execution of complex air maneuvers and rapid sequential decision making. The complexity of these decisions can increase even further when including additional weapon capabilities. The advancement of unmanned autonomous vehicle technology and weapon capabilities can help combat the hindrance that comes with human limitations. Autonomous unmanned combat aerial vehicles (AUCAVs) and the implementation of advanced weapon capabilities such as Directed Energy Weapons (DEWs) can prove to be vital in a WVR air combat context. This derives the question – Can AUCAV’s possess the proper artificial intelligence and weapon capabilities to attain …

The U.S. Army Officer-To-Unit Assignment Problem, Andrea L. Phillips

Theses and Dissertations

Every two to three years, U.S. Army officers must change duty stations, which entails a selection process based on preferences. Currently, officers are assigned to units using a stable-marriage algorithm. Two impracticalities occur within this process. First, officers are required to submit strictly ranked preferences, not allowing indifference among units. Second, the stable-marriage algorithm does not give flexibility to alternative priorities. This research focuses on two modifications to the current model. First, a mixed integer program is created that allows the user, U.S. Army Human Resources Command, to consider other priorities: unit preferences and maximum officer disappointment. Second, generated data …

U.S. Army Force Structure Optimization And Sufficiency Analysis, Francis P. Gargin

Theses and Dissertations

The United States Army perpetually deploys rotational forces across the globe in support of the National Security Strategy. These forces meet a set of discrete mission demands over an extended time period before redeploying, modernizing, and preparing for the next deployment. The U.S. Army now utilizes the Regionally Aligned Readiness and Modernization Model to execute these cyclical stages for unit deployments. Specific emphasis is placed on aligning forces against a Geographic Combatant Command, which allows units to build readiness and lethality oriented towards the same series of threats, physical terrain, and civilian considerations. This research provides an Integer Programming model …

Analysis And Optimization Of Contract Data Schema, Franklin Sun

Theses and Dissertations

agement, development, and growth of U.S Air Force assets demand extensive organizational communication and structuring. These interactions yield substantial amounts of contracting and administrative information. Over 4 million such contracts as a means towards obtaining valuable insights on Department of Defense resource usage. This set of contracting data is largely not optimized for backend service in an analytics environment. To this end, the following research evaluates the efficiency and performance of various data structuring methods. Evaluated designs include a baseline unstructured schema, a Data Mart schema, and a snowflake schema. Overall design success metrics include ease of use by end …