Operational Research Commons^™

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 …

Improving Inventory For A Large Food Service Supplier, John Krolick, Chrsitian Ingersoll, Joseph Fuentes, Harmoni Blackstock, John Miller, Alexander Contarino

Mathematica Militaris

Golden State Foods (GSF) is an international food service supplier. Their Georgia manufacturing plant currently produces thousands of condiments for restaurants across the United States. This project analyzed the inventory policies of seasonal ingredients, in order to decrease GSF’s working capital and inventory holding costs. By inputting product recipes, ingredient usage, and weekly inventory data into a dynamic lot-sizing model, we predict optimal order quantities and reorder points for GSF’s seasonal and expensive ingredients. This will potentially decrease the facility’s $1.2 million holding cost and increase its long-term profits compared to the status quo.

Prioritizing Ports And Waterways Safety Assessments (Pawsas), Matalynn Clark, Peyton Phillips, Claire Portigue, Justin Canovas, Eric Johnson, Andrew Zuckerman

Mathematica Militaris

A Ports and Waterways Safety Assessment (PAWSA) is a discussion forum facilitated by the United States Coast Guard Navigation Center (NAVCEN) to analyze the state of a port or waterway as it relates to navigation, vessel traffic, and physical attributes of the waterway. A successful workshop requires the collaboration between various stakeholders such as waterway users, environmental interest groups and local law enforcement. Without involving the relevant parties and encouraging their insight, the USCG risks creating an incomplete understanding of the port’s dynamic.

This project examines the characteristics of eight ports across the U.S. to determine which is in most …

Constrained Optimization Based Adversarial Example Generation For Transfer Attacks In Network Intrusion Detection Systems, Marc Chale, Bruce Cox, Jeffery Weir, Nathaniel D. Bastian

ACI Journal Articles

Deep learning has enabled network intrusion detection rates as high as 99.9% for malicious network packets without requiring feature engineering. Adversarial machine learning methods have been used to evade classifiers in the computer vision domain; however, existing methods do not translate well into the constrained cyber domain as they tend to produce non-functional network packets. This research views the payload of network packets as code with many functional units. A meta-heuristic based generative model is developed to maximize classification loss of packet payloads with respect to a surrogate model by repeatedly substituting units of code with functionally equivalent counterparts. The …

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 …

A Comparison Of Nonverbal And Paraverbal Behaviors In Simulated And Virtual Patient Encounters, Sarah Powers, Mark W. Scerbo, Matthew Pacailler, Macy Kisiel, Baillie Hirst, Ginger S. Watson, Lauren Hamel, Fred Kron

Modeling, Simulation and Visualization Student Capstone Conference

The present study assessed whether trainees display similar nonverbal and paraverbal behaviors when interacting with a simulated (SP) and virtual patient (VP). Sixty second slices of time following four interactions were rated for the presence and frequency of three nonverbal and paraverbal behaviors. Results revealed that students exhibited fewer behaviors in the VP interaction, possibly due to differences social inhibition or fidelity between the two formats.

Optimization Of Acrylonitrile Butadiene Styrene Filament 3d Printing Process Parameters Based On Mechanical Test, Raja S, Rajeswari N

International Journal of Mechanical and Industrial Engineering

This research paper's main goal is to improve the printing parameters that can be used in the 3D Printing Material Extrusion production method in order to get the best printing parameters for Acrylonitrile Butadiene Styrene (ABS) filament with the tensile test in the shortest possible time. The printing parameters that can be employed on 3D printing material extrusion machines include the extruder temperature, layer height, printing speed, and shell count. Also, tensile specimens in accordance with the ASTM (American Society for Testing and Materials) D638 standard were created utilizing ABS filament and the aforementioned adjusted printing settings. The most effective …

Factors Influencing Users’ Attitudes Towards Using Brain Computer Interface (Bci) For Non Medical Uses: An Application Of The Technology Acceptance Model (Tam), Yichin Wu, Leila Halawi

National Training Aircraft Symposium (NTAS)

While brain-computer interfaces (BCI) are gaining popularity in assisting people with illnesses, there is also increased technical research on incorporating BCI into healthy people’s lives. So far, not much research has focused on user attitudes, although some research has pointed out privacy and trust issues. Understanding potential users’ attitudes, expectations, and concerns early in the technology development stage is crucial for the novelty's success. For this reason, this study aims to understand the general publics’ attitude towards BCI for nonmedical uses using the technology acceptance model (TAM). The study will offer insights into how external factors including technology optimism, familiarity, …

The Sensitivity Of A Laplacian Family Of Ranking Methods, Claire S. Chang

HMC Senior Theses

Ranking from pairwise comparisons is a particularly rich subset of ranking problems. In this work, we focus on a family of ranking methods for pairwise comparisons which encompasses the well-known Massey, Colley, and Markov methods. We will accomplish two objectives to deepen our understanding of this family. First, we will consider its network diffusion interpretation. Second, we will analyze its sensitivity by studying the "maximal upset" where the direction of an arc between the highest and lowest ranked alternatives is flipped. Through these analyses, we will build intuition to answer the question "What are the characteristics of robust ranking methods?" …

Integrated Machine Learning And Optimization Approaches, Dogacan Yilmaz

Dissertations

This dissertation focuses on the integration of machine learning and optimization. Specifically, novel machine learning-based frameworks are proposed to help solve a broad range of well-known operations research problems to reduce the solution times. The first study presents a bidirectional Long Short-Term Memory framework to learn optimal solutions to sequential decision-making problems. Computational results show that the framework significantly reduces the solution time of benchmark capacitated lot-sizing problems without much loss in feasibility and optimality. Also, models trained using shorter planning horizons can successfully predict the optimal solution of the instances with longer planning horizons. For the hardest data set, …

Context-Aware Collaborative Neuro-Symbolic Inference In Internet Of Battlefield Things, Tarek Abdelzaher, Nathaniel D. Bastian, Susmit Jha, Lance Kaplan, Mani Srivastava, Venugopal Veeravalli

ACI Journal Articles

IoBTs must feature collaborative, context-aware, multi-modal fusion for real-time, robust decision-making in adversarial environments. The integration of machine learning (ML) models into IoBTs has been successful at solving these problems at a small scale (e.g., AiTR), but state-of-the-art ML models grow exponentially with increasing temporal and spatial scale of modeled phenomena, and can thus become brittle, untrustworthy, and vulnerable when interpreting large-scale tactical edge data. To address this challenge, we need to develop principles and methodologies for uncertainty-quantified neuro-symbolic ML, where learning and inference exploit symbolic knowledge and reasoning, in addition to, multi-modal and multi-vantage sensor data. The approach features …

Models And Algorithms For Trauma Network Design., Sagarkumar Dhirubhai Hirpara

Electronic Theses and Dissertations

Trauma continues to be the leading cause of death and disability in the US for people aged 44 and under, making it a major public health problem. The geographical maldistribution of Trauma Centers (TCs), and the resulting higher access time to the nearest TC, has been shown to impact trauma patient safety and increase disability or mortality. State governments often design a trauma network to provide prompt and definitive care to their citizens. However, this process is mainly manual and experience-based and often leads to a suboptimal network in terms of patient safety and resource utilization. This dissertation fills important …

Novel Mixed Integer Programming Approaches To Unit Commitment And Tool Switching Problems, Najmaddin Akhundov

Doctoral Dissertations

In the first two chapters, we discuss mixed integer programming formulations in Unit Commitment Problem. First, we present a new reformulation to capture the uncertainty associated with renewable energy. Then, the symmetrical property of UC is exploited to develop new methods to improve the computational time by reducing redundancy in the search space. In the third chapter, we focus on the Tool Switching and Sequencing Problem. Similar to UC, we analyze its symmetrical nature and present a new reformulation and symmetry-breaking cuts which lead to a significant improvement in the solution time. In chapter one, we use convex hull pricing …

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 …

On Variants Of Sliding And Frank-Wolfe Type Methods And Their Applications In Video Co-Localization, Seyed Hamid Nazari

All Dissertations

In this dissertation, our main focus is to design and analyze first-order methods for computing approximate solutions to convex, smooth optimization problems over certain feasible sets. Specifically, our goal in this dissertation is to explore some variants of sliding and Frank-Wolfe (FW) type algorithms, analyze their convergence complexity, and examine their performance in numerical experiments. We achieve three accomplishments in our research results throughout this dissertation. First, we incorporate a linesearch technique to a well-known projection-free sliding algorithm, namely the conditional gradient sliding (CGS) method. Our proposed algorithm, called the conditional gradient sliding with linesearch (CGSls), does not require the …

Implementation Of The Plan For Every Part (Pfep) Tool And Additional Methodologies For Operational Improvement., Bernardo Luis Borges Pedroso

Masters Theses

The work focused on the inventory management of Dimplex Thermal Solutions, which had a profoundly overstocked warehouse and was suffering from significant operating expenses, due to the absence of a grounded ordering policy and the need to rent external storage space, respectively.

The main objective of the thesis was to solve the primarily mentioned problems, by constructing a Plan For Every Part (PFEP) tool, followed by the application of an inventory policy and the proposal of a redesigned warehouse layout, to compute ideal stock values and calculate the footprint requirements for Dimplex’s updated inventory levels, respectively. The execution step concerned …

Off-Policy Evaluation For Action-Dependent Non-Stationary Environments, Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno Castro Da Silva, Emma Brunskill, Philip Thomas

ACI Journal Articles

Methods for sequential decision-making are often built upon a foundational assumption that the underlying decision process is stationary. This limits the application of such methods because real-world problems are often subject to changes due to external factors (passive non-stationarity), changes induced by interactions with the system itself (active non-stationarity), or both (hybrid non-stationarity). In this work, we take the first steps towards the fundamental challenge of on-policy and off-policy evaluation amidst structured changes due to active, passive, or hybrid non-stationarity. Towards this goal, we make a higher-order stationarity assumption such that non-stationarity results in changes over time, but the way …

Recall Distortion In Neural Network Pruning And The Undecayed Pruning Algorithm, Aidan Good, Jiaqi Lin, Hannah Sieg, Mikey Ferguson, Xin Yu, Shandian Zhe, Jerzy Wieczorek, Thiago Serra

Faculty Conference Papers and Presentations

Pruning techniques have been successfully used in neural networks to trade accuracy for sparsity. However, the impact of network pruning is not uniform: prior work has shown that the recall for underrepresented classes in a dataset may be more negatively affected. In this work, we study such relative distortions in recall by hypothesizing an intensification effect that is inherent to the model. Namely, that pruning makes recall relatively worse for a class with recall below accuracy and, conversely, that it makes recall relatively better for a class with recall above accuracy. In addition, we propose a new pruning algorithm aimed …

Using Strategic Options Development And Analysis (Soda) To Understand The Simulation Accessibility Problem, Andrew J. Collins, Ying Thaviphoke, Antuela A. Tako

Engineering Management & Systems Engineering Faculty Publications

Simulation modelling is applied to a wide range of problems, including defense and healthcare. However, there is a concern within the simulation community that there is a limited use and implementation of simulation studies in practice. This suggests that despite its benefits, simulation may not be reaching its potential in making a real-world impact. The main reason for this could be that simulation tools are not widely accessible in industry. In this paper, we investigate the issues that affect simulation modelling accessibility through a workshop with simulation practitioners. We use Strategic Options Development and Analysis (SODA), a problem-structuring approach that …

Study Of Stochastic Market Clearing Problems In Power Systems With High Renewable Integration, Saumya Sakitha Sashrika Ariyarathne

Operations Research and Engineering Management Theses and Dissertations

Integrating large-scale renewable energy resources into the power grid poses several operational and economic problems due to their inherently stochastic nature. The lack of predictability of renewable outputs deteriorates the power grid’s reliability. The power system operators have recognized this need to account for uncertainty in making operational decisions and forming electricity pricing. In this regard, this dissertation studies three aspects that aid large-scale renewable integration into power systems. 1. We develop a nonparametric change point-based statistical model to generate scenarios that accurately capture the renewable generation stochastic processes; 2. We design new pricing mechanisms derived from alternative stochastic programming …