Operations Research, Systems Engineering and Industrial Engineering Commons^™

Topics In Optimization For Sustainable Energy Planning, Bahareh Nasirian

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

ABSTRACT: Due to the current trend of rising energy demand, finding alternate energy sources is vital. Many cities consider renewable energy as a component of a sustainable future. Typically, organic wastes are considered renewable energy sources. Wastes can be converted to proper energy forms using waste-to-energy technologies. On the other hand, more renewable energy sources in the power system may increase energy market stochasticity, alter system operation, and pose new problems for the current supply and demand equilibrium, which consequently requires new control methods. Hence, taking into account the issues mentioned above, in this research, we address organic waste conversion …

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 …

Editorial: Innovative Shared Transportation, Marco Nie, Hai Wang, Wai Yuen Szeto

Research Collection School Of Computing and Information Systems

Recent technological developments—mobile computing, autonomous driving, alternative fuel vehicles, and blockchain, to name a few—have enabled numerous innovations in mobility, transportation, and logistics services. They offer unprecedented opportunities to transform conventional transportation systems, for both personal travel and freight logistics, with novel solutions. Of these solutions, those built on the emerging concept of shared economy, such as Uber, Didi, and Cargostream, have received much attention recently. The rapidly expanding scope of shared transportation services now includes ride-sourcing, ridesharing, car sharing, hitch service, flexible paratransit, shared freight delivery, shared logistics, bike sharing, shared last-mile service, parking space sharing, and so on.

Optimizing Locations And Sizes Of Asphalt Concrete Plants In Karbala, Iraq, Ghayath Ali, Sawsan R Mohammad, Alaa M. Abdulhussein

Al-Bahir

This study develops and presents a methodology for determining the optimal geographic distribution and size of asphalt concrete plants in Karbala, Iraq, in order to minimize the cost of asphalt concrete produced. The purpose of this study is to discuss these points. The methodology can identify potential locations for asphalt concrete plants within a study area, considering the plants' operation and capital costs and the costs of transporting raw materials to the plants and asphalt concrete to demand centers. Matrix Laboratory (MATLAB) software have been used to program the methodology. This methodology has been applied to Karbala using actual data. …

Team And Skill Matching For Disaster Recovery Operations, Emily B. Frahm

Theses and Dissertations

United States Air Force (USAF) bases are key power projection platforms that ensure mission readiness and help bring humanitarian aid to locations in need. Recovering airfields after attack or natural disaster is a key mission of USAF civil engineers, and accomplishing this repair as swiftly as possible is key to maintaining our position in the global order. Accomplishing a disaster recovery project is a set of teams, each assigned to a specific task, and made up of a series of personnel. The question answered within this paper is: how do we match the right person with the appropriate skills to …

Techno-Economic Analysis And Optimization Of Hydrogen And Mechanical Energy Storage Systems, Pavitra Senthamilselvan Sengalani

Graduate Theses, Dissertations, and Problem Reports (ETD)

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

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

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 …

Advancing Statistical Learning And Decision Modeling Using Irregularly-Sampled Multivariate Data For Managing Respiratory Diseases, Maryam Alimohammadi

Graduate Theses and Dissertations

Complex healthcare systems require efficient and effective data-driven decision making in various aspects. As patient data becomes more available, advanced statistical learning and machine learning techniques are applied to improve data-driven decision making. However, patient health data, including clinical trial data, medical records, and electronic health records, are associated with several challenges. Patient health data includes medical information of a patient that may includedemographics, information relating to their health or illness, medications and treatments, etc. They are a combination of static and time series variables, with many censoring and missingness in the data, and are irregularly sampled in most cases. …

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 …

Lasso Based State Transition Modeling With Interactions In Adaptive Interdisciplinary Pain Management, Amith Viswanatha

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

The Eugene McDermott Center for Pain Management at the University of Texas Southwestern Medical Center has an interdisciplinary pain management program for chronic pain. This program treats patients with a holistic view of reducing chronic pain and improving their physical, mental, and social well-being through treatment interventions. The development of an adaptive treatment decision tool is main goal of the research project. This program is modeled as a two-stage adaptive treatment decision problem, with state transition models representing the transition of patient state, treatment, and outcome variables from stage 1 to stage 2. Interactions between the patient state and treatments …

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

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

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

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

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 …

Academic Advising Support Tool: An Optimization Approach, Spencer Loper

Industrial Engineering Undergraduate Honors Theses

More than ever, a college education is necessary to remain competitive in the job market. Therefore, colleges are dedicating numerous resources to ensure student success. Nonetheless, one of the most important factors of student success is proper academic advising. Students at the University of Arkansas and more specifically within the department of Industrial Engineering department are fortunate to have access to fantastic advising. However, given the volume of students, academic advisors do not have the time to talk through the nuance of every student’s long-term academic plan. The department does provide an eight-semester plan; however, students who have deviated from …

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 …

Simulation-Based Optimization: Implications Of Complex Adaptive Systems And Deep Uncertainty, Andreas Tolk

VMASC Publications

Within the modeling and simulation community, simulation-based optimization has often been successfully used to improve productivity and business processes. However, the increased importance of using simulation to better understand complex adaptive systems and address operations research questions characterized by deep uncertainty, such as the need for policy support within socio-technical systems, leads to the necessity to revisit the way simulation can be applied in this new area. Similar observations can be made for complex adaptive systems that constantly change their behavior, which is reflected in a continually changing solution space. Deep uncertainty describes problems with inadequate or incomplete information about …

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

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

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

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 …

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 …

Scheduling Allocation And Inventory Replenishment Problems Under Uncertainty: Applications In Managing Electric Vehicle And Drone Battery Swap Stations, Amin Asadi

Graduate Theses and Dissertations

In this dissertation, motivated by electric vehicle (EV) and drone application growth, we propose novel optimization problems and solution techniques for managing the operations at EV and drone battery swap stations. In Chapter 2, we introduce a novel class of stochastic scheduling allocation and inventory replenishment problems (SAIRP), which determines the recharging, discharging, and replacement decisions at a swap station over time to maximize the expected total profit. We use Markov Decision Process (MDP) to model SAIRPs facing uncertain demands, varying costs, and battery degradation. Considering battery degradation is crucial as it relaxes the assumption that charging/discharging batteries do not …

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 …

Yard Layout Optimization For General Cargo Terminal, Zhixiong Liu, Dong Yu, Chunjun Zhang

Journal of System Simulation

Abstract: Yard layout is an important component of the port yard allocation decision which affects the cargo storage capacity and through capacity for the port yard. As to the general cargo yard, combined with the cargo type and the yard storage strategy, the yard layout optimization model for the general cargo terminal is presented based on the statistical analysis for the production data when the optimization aim is minimizing the total horizontal transport distance of the trailer. The yard layout optimization results are employed by the mathematical tool Gurobi for different storage strategies, and the yard layout optimization results are …

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 …

A Survey Of Edge Computing Resource Allocation And Task Scheduling Optimization, Wang Ling, Chuge Wu, Wenhui Fan

Journal of System Simulation

Abstract: With the rapid development of Internet of Things (IoT) and mobile terminals, the concept of edge computing arises. By moving the computation and storage capacity to the edge of network, edge computing is able to deal with a large amount of data produced by IoT devices and the responsive request from IoT application. To improve the utility of edge resource, the quality of service and quality of user experience, resource allocation and task scheduling optimization problems under edge computing attract wide attention. It becomes more difficult due to the geographic separated and heterogeneous features of edge computing resource as …