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Articles 1 - 30 of 116
Full-Text Articles in Engineering
Sequential Optimization For Stressor-Informed Test Planning Through Integration Of Experimental And Simulated Data, Jacob Brecheisen
Sequential Optimization For Stressor-Informed Test Planning Through Integration Of Experimental And Simulated Data, Jacob Brecheisen
Data Science Undergraduate Honors Theses
This technical report details an innovative approach in reliability engineering aimed at maximizing system durability through a synergistic use of physical experimentation and computer-based modeling. Our methodology explores the efficient design and analysis of computer experiments and physical tests to facilitate accelerated reliability growth, while leveraging a sequential integration of data from these two distinct sources: costly physical experiments, characterized by random errors, and inexpensive computer simulations, marked by inherent systematic errors. The key innovation lies in the adoption of a closed-loop design and analysis method. This method begins by identifying a viable subset of important environmental stressors—such as temperature, …
Optimization Of Human Interactions In The College Campus Model Via Simio Integration, Benjamin E. Chaback
Optimization Of Human Interactions In The College Campus Model Via Simio Integration, Benjamin E. Chaback
Doctoral Dissertations and Master's Theses
College campuses are a significant part of life in some cities. Many students each year attend university, pursuing additional knowledge from faculty members. Both staff and faculty members rely on these students to have successful jobs and to ensure the university functions. Yet recently, more and more students are attending, leading to overcrowding, lower admission rates, and difficulty getting into good programs. Previous work exists on qualitative student affairs and quantitative retention data, yet little on using simulations to model this problem. This work aimed to (a) Determine the ability to successfully model human interactions/people flow on a college campus, …
Imerys: Tube Mill Optimization Project, Ryan Waltman, Dalton Beasley, Dyson Beasley, Tristan Mcmichael
Imerys: Tube Mill Optimization Project, Ryan Waltman, Dalton Beasley, Dyson Beasley, Tristan Mcmichael
Senior Design Project For Engineers
The Tube Mill Optimization Project is in partnership with Imerys for Tube Mill 81 at their Marble Hill site in Georgia. Tube Mill 81 is a dry ball mill that operates 24/7 and makes an intermediary product for Plant 3. Tube Mill 81 needs quality improvement and a production rate increase to meet demand. Imerys’s quality specification is between a particle size of 12-18 microns and an acceptable production rate of 5 tons per hour. This project focuses on the development and implementation of three solutions: increase the amps on the separator to increase production, replace missing classifier blades in …
Utilization Of Integer Programming For Scheduling Maintenance At Nuclear Power Plants, Timothy Gallacher
Utilization Of Integer Programming For Scheduling Maintenance At Nuclear Power Plants, Timothy Gallacher
Doctoral Dissertations
This thesis develops a thought that naturally explores three specific motifs for solving the complexities of scheduling maintenance at Nuclear Power Plants (NPP). The first chapter of this paper will develop the initial thought around creating a schedule for a given work week, including all the various constraints inherent to this problem. Such constraints include but are not limited to personnel availability, allowable component out-of-service time, and the Plant Risk Assessment. The objective function being to minimize the total cost of worker’s compensation for that given week.
The second chapter addresses the question of whether this simple schedule can be …
Resource Allocation In Subsidy Welfare Programs: Managerial Insights For Nonprofits, Governments, And Service Providers, Wei Wei
Doctoral Dissertations
Subsidy welfare programs provide financial assistance to economically disadvantaged individuals and families to access essential and life-altering services (e.g., education, child care, and housing) that they might not otherwise have access to. Access to these services is considered critical to achieving a better and more sustainable future for all. As such, these high-quality services are directly related to several United Nations Sustainable Development Goals, which were adopted as a universal call to action to end poverty, save the planet and improve the lives and prospects of everyone, everywhere." In particular, the need for these affordable and high-quality services has been …
Improving Mobility And Safety In Traditional And Intelligent Transportation Systems Using Computational And Mathematical Modeling, Shahrbanoo Rezaei
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
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 …
Exploiting Symmetry In Linear And Integer Linear Programming, Ethan Jedidiah Deakins
Exploiting Symmetry In Linear And Integer Linear Programming, Ethan Jedidiah Deakins
Doctoral Dissertations
This thesis explores two algorithmic approaches for exploiting symmetries in linear and integer linear programs. The first is orbital crossover, a novel method of crossover designed to exploit symmetry in linear programs. Symmetry has long been considered a curse in combinatorial optimization problems, but significant progress has been made. Up until recently, symmetry exploitation in linear programs was not worth the upfront cost of symmetry detection. However, recent results involving a generalization of symmetries, equitable partitions, has made the upfront cost much more manageable.
The motivation for orbital crossover is that many highly symmetric integer linear programs exist, and …
A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb
A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb
Masters Theses
One of the biggest challenges the clinical research industry currently faces is the accurate forecasting of patient enrollment (namely if and when a clinical trial will achieve full enrollment), as the stochastic behavior of enrollment can significantly contribute to delays in the development of new drugs, increases in duration and costs of clinical trials, and the over- or under- estimation of clinical supply. This study proposes a Machine Learning model using a Fully Convolutional Network (FCN) that is trained on a dataset of 100,000 patient enrollment data points including patient age, patient gender, patient disease, investigational product, study phase, blinded …
Techno-Economic Analysis And Optimization Of Hydrogen And Mechanical Energy Storage Systems, Pavitra Senthamilselvan Sengalani
Techno-Economic Analysis And Optimization Of Hydrogen And Mechanical Energy Storage Systems, Pavitra Senthamilselvan Sengalani
Graduate Theses, Dissertations, and Problem Reports
The increasing significance of renewable energy sources is thrusting the load cycling of fossil-fueled power plants (FFPP), designed to operate under nominal-load conditions. Integration of energy storage systems (ESS) with the FFPPs such as hydrogen energy storage (HES) and mechanical energy storage facility such as compressed air energy storage (CAES) shows the potential to minimize the levelized cost of electricity during high demand scenarios and also minimize the negative impacts of off-design FFPP operation. The deployment of energy storage facilities at the FFPP level have considerable potential advantages as they can be exploited within the existing equipment items and facilities …
Analyzing The Supply Chain Operation Of A Fast-Food Restaurant Using Simulation Modeling And Developing A Cost Estimation Optimization Model In The Disruption Period, Amit Kumar Saha
Open Access Theses & Dissertations
Supply chain operation performance is a much-discussed topic over the last decade which will lead to optimizing the resources required to provide the necessary level of customer service to a specific segment and improve customer service through increased product availability and reduced order cycle time. During disruption in supply chain, performance parameter changes, and the overall supply chain cost at each stage increases. External factors such as labor shortages, delayed and costly supplies, and decreased demand also contribute to this cost. This thesis work presents a research-focused analysis of a small pizza shop, under circumstances that include the loss of …
Essays On Perioperative Services Problems In Healthcare, Amogh S. Bhosekar
Essays On Perioperative Services Problems In Healthcare, Amogh S. Bhosekar
All Dissertations
One of the critical challenges in healthcare operations management is to efficiently utilize the expensive resources needed while maintaining the quality of care provided. Simulation and optimization methods can be effectively used to provide better healthcare services. This can be achieved by developing models to minimize patient waiting times, minimize healthcare supply chain and logistics costs, and maximize access. In this proposal, we study some of the important problems in healthcare operations management. More specifically, we focus on perioperative services and study scheduling of operating rooms (ORs) and management of necessary resources such as staff, equipment, and surgical instruments. We …
Cooperative Wide Area Search Algorithm Analysis Using Sub-Region Techniques, Shawn Whitney
Cooperative Wide Area Search Algorithm Analysis Using Sub-Region Techniques, Shawn Whitney
Theses and Dissertations
Recent advances in small Unmmaned Aerial Vehicle (UAV) technology reinvigorates the need for additional research into Wide Area Search (WAS) algorithms for civilian and military applications. But due to the extremely large variability in UAV environments and design, Digital Engineering (DE) is utilized to reduce the time, cost, and energy required to advance this technology. DE also allows rapid design and evaluation of autonomous systems which utilize and support WAS algorithms. Modern WAS algorithms can be broadly classified into decision-based algorithms, statistical algorithms, and Artificial Intelligence (AI)/Machine Learning (ML) algorithms. This research continues on the work by Hatzinger and Gertsman …
Developing Novel Optimization And Machine Learning Frameworks To Improve And Assess The Safety Of Workplaces, Amin Aghalari
Developing Novel Optimization And Machine Learning Frameworks To Improve And Assess The Safety Of Workplaces, Amin Aghalari
Theses and Dissertations
This study proposes several decision-making tools utilizing optimization and machine learning frameworks to assess and improve the safety of the workplaces. The first chapter of this study presents a novel mathematical model to optimally locate a set of detectors to minimize the expected number of casualties in a given threat area. The problem is formulated as a nonlinear binary integer programming model and then solved as a linearized branch-and-bound algorithm. Several sensitivity analyses illustrate the model's robustness and draw key managerial insights. One of the prevailing threats in the last decades, Active Shooting (AS) violence, poses a serious threat to …
Optimal Global Supply Chain And Warehouse Planning Under Uncertainty, Avnish Kishor Malde
Optimal Global Supply Chain And Warehouse Planning Under Uncertainty, Avnish Kishor Malde
All Dissertations
A manufacturing company's inbound supply chain consists of various processes such as procurement, consolidation, and warehousing. Each of these processes is the focus of a different chapter in this dissertation.
The manufacturer depends on its suppliers to provide the raw materials and parts required to manufacture a finished product. These suppliers can be located locally or overseas with respect to the manufacturer's geographic location. The ordering and transportation lead times are shorter if the supplier is located locally. Just In Time (JIT) or Just In Sequence (JIS) inventory management methods could be practiced by the manufacturer to procure the raw …
Development Of Software Tools For Efficient And Sustainable Process Development And Improvement, Jake P. Stengel
Development Of Software Tools For Efficient And Sustainable Process Development And Improvement, Jake P. Stengel
Theses and Dissertations
Infrastructure is a key component in the well-being of our society that leads to its growth, development, and productive operations. A well-built infrastructure allows the community to be more competitive and promotes economic advancement. In 2021, the ASCE (American Society of Civil Engineers) ranked the American infrastructure as substandard, with an overall grade of C-. The overall ranking suffers when key infrastructure categories are not maintained according to the needs of the population. Therefore, there is a need to consider alternative methods to improve our infrastructure and make it more sustainable to enhance the overall grade. One of the challenges …
An Optimization Modeling Framework To Evaluate Civilians Response Under Active Shooter Violence Situations, Joseph G. Kerlin
An Optimization Modeling Framework To Evaluate Civilians Response Under Active Shooter Violence Situations, Joseph G. Kerlin
Theses and Dissertations
Workplace safety is under serious threat due to the increasing trend of active shooter violence in recent years. Therefore, it becomes essential that the safety of a workplace is rigorously and, most importantly, methodologically assessed against active shooter violence. To serve this purpose, this study proposes a machine learning-optimization framework to assess the safety of a building against possible active shooter violence. First, several state-of-the-art machine learning models are employed to predict an agent’s movement decisions (with directions) under different violence scenarios. The predictions are then utilized in a mixed-integer linear programming model to maximize the agent’s utility under a …
Investigations Of External Resources And The Impact Of Imaging On Patient Flow In The Emergency Department, Marisa Shehan
Investigations Of External Resources And The Impact Of Imaging On Patient Flow In The Emergency Department, Marisa Shehan
All Theses
The problems associated with Emergency Department (ED) crowding are numerous, varied, and complex. Though overcrowded Emergency Departments are frequently attributed to overcrowded hospitals, crowding is also impacted by bottlenecks in patient flow. While discrete-event simulation (DES) is commonly used to model ED flow, external resources are typically excluded from these models due to their complexity and the limited amount of known information for these processes. Instead, external resources such as consults, labs, and imaging are modeled using estimation and/or educated guesswork. In this study, the impact of imaging on patient flow was assessed through data analysis of specific imaging factors, …
Interdiction Models To Disrupt The Operations Of Sex Trafficking And Other Forced Illicit Labor Networks, Michael T. Clark
Interdiction Models To Disrupt The Operations Of Sex Trafficking And Other Forced Illicit Labor Networks, Michael T. Clark
All Theses
Sex traffickers often force their victims to work in both commercial sex markets and perform other illicit activities (e.g., drug dealing, theft, and fraud). Current literature has failed to address interdiction models that aim to disrupt all components of a sex traffickers’ operation, including these other illicit activities. In this thesis, we present a interdiction problem, and its single-level linear optimization reformulation, to reduce the profit of a human trafficking network concurrently operating in the commercial sex market and other illicit activity markets. Our novel formulation aims to investigate the practical implications of interdiction decisions made to disrupt a human …
A New Approach To Career Field Matching For Commissioning Air Force Cadets, Daniel Griffen Laird
A New Approach To Career Field Matching For Commissioning Air Force Cadets, Daniel Griffen Laird
Theses and Dissertations
The current method of assigning graduating cadets from the United States Air Force Academy and Reserve Officers' Training Corps (ROTC) detachments to their career fields uses an integer programming model to maximize \global" Air Force utility, subject to several Air Force-defined constraints. This utility evaluates the positive benefit of assigning a certain cadet to a certain career field. This paper discusses the issues with such a model, as well as presents a new, more refined approach to the problem. Rather than provide a one-size-fits-all formulation of this particular assignment problem, a Value-Focused Thinking (VFT) framework is applied, in conjunction with …
Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa
Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa
Theses and Dissertations
“Energy Trilemma” has recently received an increasing concern among policy makers. The trilemma conceptual framework is based on three main dimensions: environmental sustainability, energy equity, and energy security. Energy security reflects a nation’s capability to meet current and future energy demand. Rational energy planning is thus a fundamental aspect to articulate energy policies. The energy system is huge and complex, accordingly in order to guarantee the availability of energy supply, it is necessary to implement strategies on the consumption side. Energy modeling is a tool that helps policy makers and researchers understand the fluctuations in the energy system. Over the …
Development Of Metaheuristic Algorithms For The Efficient Allocation Of Power Flow Control Devices, Eduardo Jose Castillo Fatule
Development Of Metaheuristic Algorithms For The Efficient Allocation Of Power Flow Control Devices, Eduardo Jose Castillo Fatule
Open Access Theses & Dissertations
Modern energy grids have become extremely complex systems, requiring more variable and active flow control. As a remedy to this, Distributed Flexible AC Transmission Systems (D-FACTS) are cost-efficient devices used to mitigate power flow congestion and integrate renewable energies. The objective of this research is then to propose an efficient multiple objective evolutionary algorithm to solve a stochastic model for D-FACTS allocation, which aims to optimize various objectives related to cost, grid health, and environmental impacts. The model was implemented on a modified RTS-96 test system, and the results show that optimally allocating D-FACTS modules using the proposed model can …
Drone Location And Scheduling Problems In Humanitarian Logistics., Zabih Ghelichi
Drone Location And Scheduling Problems In Humanitarian Logistics., Zabih Ghelichi
Electronic Theses and Dissertations
Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, are a promising technology for the last-mile delivery of medical and aid items in humanitarian logistics. In emergency scenarios, like disasters, where transportation networks are destroyed and people are stranded, drones can accelerate the delivery of urgently needed items, e.g., food and water, insulin shots and blood pressure pills, to those trapped in the disaster-affected areas. Drones can also provide logistics services in many non-emergency situations by delivering medical items, e.g., vaccine shots and lab specimens, to remote communities and hard-to-access locations. The contribution of using UAVs goes beyond merely having …
Interdependent Infrastructure Recovery Using Multilayered Networks And Optimization, Brigham A. Moore
Interdependent Infrastructure Recovery Using Multilayered Networks And Optimization, Brigham A. Moore
Theses and Dissertations
Interdependent infrastructure recovery modeling and simulation are complicated due to various interdependent connections and complexities. Current efforts have identified both operational and restoration interdependency subtypes and coupling strategies that have not been integrated into one comprehensive model. This research presents a model which simultaneously integrates nine interdependency subtypes and four coupling strategies in a multi-objective format to provide the most tailorable and comprehensive network-based recovery model available. This research also created a defense-centric interdependent infrastructure database by modifying the existing CLARC database. This research then addressed assumptions regarding recovery work management in order to address the impact of work crew …
Multi-Objective Optimization Of Green Transportation Operations In Supply Chain Management, Nayera Elgharably
Multi-Objective Optimization Of Green Transportation Operations In Supply Chain Management, Nayera Elgharably
Electronic Thesis and Dissertation Repository
Supply chain is the integration of manufacturing process where raw materials are converted into final products, then delivered to customers. Supply chains consists of two basic integrated process that interact together: (1) production and inventory and (2) distribution and logistics. Maximizing competitiveness and profitability are of the main goals of a supply chain. Accounting only for economic impacts as variable and fixed costs does not serve the main goal of the supply chain. Therefore, considering customer satisfaction measures in distribution models is essential in supply chain management. Models that addressed the three objectives simultaneously handled one of the objectives as …
Enabling The “Easy Button” For Broad, Parallel Optimization Of Functions Evaluated By Simulation, Andrew Gibson
Enabling The “Easy Button” For Broad, Parallel Optimization Of Functions Evaluated By Simulation, Andrew Gibson
Graduate Theses and Dissertations
Java Optimization by Simulation (JOBS) is presented: an open-source, object-oriented Java library designed to enable the study, research, and use of optimization for models evaluated by simulation. JOBS includes several novel design features that make it easy for a simulation modeler, without extensive expertise in optimization or parallel computation, to define an optimization model with deterministic and/or stochastic constraints, choose one or more metaheuristics to solve it and run, using massively parallel function evaluation to reduce wall-clock times.
JOBS is supported by a new language independent, application programming interface (API) for remote simulation model evaluation and a serverless computing environment …
Optimization Of Vaccine Supply Chains In Low- And Middle-Income Countries Utilizing Drones, Maximilian Kolter
Optimization Of Vaccine Supply Chains In Low- And Middle-Income Countries Utilizing Drones, Maximilian Kolter
Graduate Theses and Dissertations
Despite tremendous efforts from governments and humanitarian organizations, millions of children in low- and low-middle-income countries (LICs and LMICs) are still excluded from the benefits of immunization. The vaccine distribution in LICs and LMICs is challenging for several reasons, such as limited cold chain capacities, vaccine wastage, uncertain demand, and lack of access to immunization services. A promising avenue to address these issues is the utilization of drones for vaccine delivery. Drones can fly at high speed on direct paths and could enable on-demand deliveries to mitigate limited storage capacities. Further, their independence of road networks could allow them reaching …
Optimizing Garbage Pick-Up In Wahoo, Ne, Andrew Pace
Optimizing Garbage Pick-Up In Wahoo, Ne, Andrew Pace
Theses/Capstones/Creative Projects
This project seeks to optimize the garbage pickup routes of Roadrunner Transportation in Wahoo, Nebraska using operations research and optimization tools. Currently, the company has no formal procedure for determining these routes. Roadrunner Transportation would like to expand their operation and to do so in the most efficient manner. To determine efficient routes, the Capacitated Vehicle Routing Problem (CVRP) is applied, and a solution to this problem is obtained by implementing a simulated annealing heuristic algorithm. Results show that a total distance of approximately 70 miles can be obtained by this implementation using a small subset of the data provided …
Optimal Communication Structures For Concurrent Computing, Andrii Berdnikov
Optimal Communication Structures For Concurrent Computing, Andrii Berdnikov
Doctoral Dissertations
This research focuses on communicative solvers that run concurrently and exchange information to improve performance. This “team of solvers” enables individual algorithms to communicate information regarding their progress and intermediate solutions, and allows them to synchronize memory structures with more “successful” counterparts. The result is that fewer nodes spend computational resources on “struggling” processes. The research is focused on optimization of communication structures that maximize algorithmic efficiency using the theoretical framework of Markov chains. Existing research addressing communication between the cooperative solvers on parallel systems lacks generality: Most studies consider a limited number of communication topologies and strategies, while the …
Optimizing Cost And Performance Of Infrastrucure Alternatives At Contingency Bases In A Hub-And-Spoke Network, Kyle J. Rodriguez
Optimizing Cost And Performance Of Infrastrucure Alternatives At Contingency Bases In A Hub-And-Spoke Network, Kyle J. Rodriguez
Theses and Dissertations
Military contingency bases require substantial resources and funding sustain and are often not connected to an infrastructure grid. Infrastructure assets produce the required outputs for sustainment, but are often expensive and inefficient, producing a significant logistical burden. With the increasing near-peer threats of opposing military forces, there is a need for more self-sufficient contingency bases with alternatives that reduce resources usage and the cost of sustainment. Accordingly, the goal of this research is to develop an optimization model capable of selecting infrastructure alternative combinations that minimize the overall resource usage and cost of sustainment at the contingency base level.