Operations Research, Systems Engineering and Industrial Engineering Commons^™

Modeling Individual Self-Protective Behavior During Epidemics, Geonsik Yu, Michael J. Garee, Mario Ventresca, Yuehwern Yih

Faculty Publications

Protecting public health from infectious diseases requires collective action, as individual behaviors—such as vaccination and mask-wearing—directly influence disease dynamics. During the COVID-19 pandemic, unexpected public responses often undermined the effectiveness of interventions, highlighting the need to understand collective behavioral patterns and motivations to design more effective mitigation strategies. This study presents an agent-based simulation model that captures how individuals adjust self-protective behaviors based on evolving opinions about disease risk and examines how these decisions interact with external factors, such as public health interventions, to shape collective outcomes. To improve the representativeness of the simulated population, multiple datasets were integrated to …

Finding The Shortest And Optimal Path With Metaheuristic And Madm Methods, Narmin Ibrahim Hasanli

Chemical Technology, Control and Management

The article had described a method for finding the shortest and most optimal path among cities. The data had been taken from the TSPLIB library, which had provided standard examples for the Traveling Salesman Problem. This approach had integrated the advantages of the meta-heuristic technique and the Multi Attribute Decision Making method to solve the problem effectively. In the first stage, the population based meta-heuristic method ACO (Ant Colony Optimization) had found optimal solutions in large search spaces. The use of pheromone trails, heuristic information and an iterative search process had given the opportunity to find the best or near-best …

A Comprehensive Academic And Industrial Survey Of Blockchain Technology For The Energy Sector Using Fuzzy Einstein Decision-Making, Umit Cali, Annabelle Lee, Barry Hayes, Claudio Lima, D. Jonathan Sebastian-Cardenas, David Flynn, Emre Kantar, Farrokh Rahimi, Kaung Si Thu, Marco Pasetti, Marthe Fogstad Dynge, Merlinda Andoni, Muhammet Deveci, Murat Kuzlu, Raquel Alanso, Kim-Kwang Raymond Choo, Sambeet Mishra, Shammya Shananda Saha, Sonam Norbu, Srinikhil Gourisetti, Ugur Halden, Vahid Hosseinezhad, Valentin Robu

Engineering Technology Faculty Publications

The global energy sector is undergoing a significant transformation driven by decarbonization and digitalization, leading to the emergence of Distributed Ledger Technology (DLT) — particularly blockchain — as a promising tool for enhancing transparency, security, and efficiency in modern power systems. This study aims to provide a comprehensive academic and industrial survey of blockchain applications in the energy sector and develop a robust decision-making framework to identify and prioritize the most promising real-world use cases based on multidisciplinary criteria. A three-stage methodology was adopted: (i) a literature and market review encompassing over 300 academic publications and commercial blockchain initiatives in …

Navigating The Complexities Of Engineering Management: Insights Into Metrics, Measurements, And Pitfalls, Charles Daniels

Engineering Management & Systems Engineering Faculty Publications

In the realm of Engineering Management, the reliance on metrics and measurements stands as a cornerstone for effective decision-making processes. These quantitative tools offer insights into performance dynamics and facilitate informed strategic choices. However, the uncritical application of metrics devoid of profound domain expertise presents significant challenges. This abstract explores the pitfalls inherent in utilizing metrics and measurements within Engineering Management without comprehensive understanding, emphasizing the potential consequences and proposing strategies for navigating this complex terrain.

Machine Learning In Requirements Elicitation: A Literature Review, Cheligeer Cheligeer, Jingwei Huang, Guosong Wu, Nadia Bhuiyan, Yuan Xu, Yong Zeng

Engineering Management & Systems Engineering Faculty Publications

A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studies that incorporate ML and natural language processing (NLP) into demand elicitation. We answer the following research questions: (1) What requirement elicitation activities are supported by ML? (2) What data sources are used to build ML-based requirement solutions? (3) What technologies, algorithms, and tools are used to build ML-based requirement elicitation? (4) How to construct an ML-based requirements elicitation method? (5) What are the available tools to support ML-based requirements elicitation methodology? Keywords …

A Systematic Stakeholder-Driven Framework For Empirical Characterization And Parameterization Of Human Agents For Agent-Based Modeling Of Older Adults' Transportation, Nilufer Oran Gibson

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Standard of living for health and well-being of oneself and of one’s family is a human right. Vulnerable populations are incapable of maintaining an adequate standard of living due to several reasons, such as financial constraints, racial profiling, health conditions, aging, and the combination of these reasons. To alleviate their vulnerability, the most basic needs of the vulnerable populations must be met. Transportation is the essential link to the resources to address the basic needs of the vulnerable populations. Transportation solutions tailored for vulnerable populations to meet their basic needs have multiple dimensions that require the involvement of all government …

Stochastic Programming And Agent-Based Simulation Approaches For Epidemics Control And Logistics Planning, Xuecheng Yin

Dissertations

This dissertation addresses the resource allocation challenges of fighting against infectious disease outbreaks. The goal of this dissertation is to formulate multi-stage stochastic programming and agent-based models to address the limitations of former literature in optimizing resource allocation for preventing and controlling epidemics and pandemics. In the first study, a multi-stage stochastic programming compartmental model is presented to integrate the uncertain disease progression and the logistics of resource allocation to control a highly contagious infectious disease. The proposed multi-stage stochastic program, which involves various disease growth scenarios, optimizes the distribution of treatment centers and resources while minimizing the total expected …

Enterprise Engineering And Intellectual Technologies For Lifecycle Management Of Industrial Production, Nodirbek Rustambekovich Yusupbekov, Valery Borisovich Tarasov, Shukhrat Manapovich Gulyamov, Fahritdin Raupovich Abdurasulov

Chemical Technology, Control and Management

The fundamental scientific problem of the development of the mathematical foundations of engineering for industrial enterprises and the development of mathematical methods of production management, as well as the creation of intelligent systems for coordinated management of the life cycles of products and production in the network of enterprises are discussed. The issues in demand in the development of a vast interdisciplinary field of enterprise engineering and the development of modern network enterprises and intelligent production using mathematical modeling methods are discussed.

Online Traffic Signal Control Through Sample-Based Constrained Optimization, Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh

Research Collection School Of Computing and Information Systems

Traffic congestion reduces productivity of individuals by increasing time spent in traffic and also increases pollution. To reduce traffic congestion by better handling dynamic traffic patterns, recent work has focused on online traffic signal control. Typically, the objective in traffic signal control is to minimize expected delay over all vehicles given the uncertainty associated with the vehicle turn movements at intersections. In order to ensure responsiveness in decision making, a typical approach is to compute a schedule that minimizes the delay for the expected scenario of vehicle movements instead of minimizing expected delay over the feasible vehicle movement scenarios. Such …

Preferred Treatment Methods For Patients With Inflammatory Bowel Disease, James L. Deitschel

Theses and Dissertations

Shared decision making is the concept of physicians involving patients in the treatment planning process. The University of Maryland Medical Center is interested in applying shared decision making to the treatment of patients with Inflammatory Bowel Disease (IBD). The two treatment methods analyzed in this study were medical management and surgery. To explore patient preferences between these two alternatives, a discrete choice experiment (DCE) was employed. The responses for the DCE were binary, so logistic regression models were explored. The conditional logistic regression model was determined to be the most appropriate for this analysis. After step-wise regression was performed, a …

Disaster Damage Categorization Applying Satellite Images And Machine Learning Algorithm, Farinaz Sabz Ali Pour, Adrian Gheorghe

Engineering Management & Systems Engineering Faculty Publications

Special information has a significant role in disaster management. Land cover mapping can detect short- and long-term changes and monitor the vulnerable habitats. It is an effective evaluation to be included in the disaster management system to protect the conservation areas. The critical visual and statistical information presented to the decision-makers can help in mitigation or adaption before crossing a threshold. This paper aims to contribute in the academic and the practice aspects by offering a potential solution to enhance the disaster data source effectiveness. The key research question that the authors try to answer in this paper is how …

Decision-Making Method For Formulating Spares Reserve Scheme Based On Deep Neural Network, Yunjing Zhang, Guangming Tang, Xiaoyu Xu

Journal of System Simulation

Abstract: Spare parts classification is important for spare parts storage and is a key part of spare parts decision-making activities. This paper analyzes the factors affecting the reserve scheme of wartime spares. Then by analyzing the inherent attributes of wartime spares, two methods of spare parts classification are proposed to determine the variety and quantity of wartime spares based on deep neural network: (1) Ranks wartime spares according to their importance. A relatively simple deep neural network is used to analyze every attribute of the wartime spares in turn; (2) Inputs all the attributes of wartime spares into a relatively …

Natural Resources Governance Employing Blockchain-Based Decision-Making, Farinaz Sabz Ali Pour, Adrian Gheorghe

Engineering Management & Systems Engineering Faculty Publications

Natural resources are essential structures of socio-economic systems which shape the well-being of humanity, environment, and the economy. Human actions have become the critical responsibility for environmental changes and pressuring many planetary boundaries. Having a systematic approach can provide a governance platform including the inherent characteristics of the resource, the historically established form of use, and transaction costs. A natural resource governance framework is developed by applying Blockchain technology as the primary goal of this study to regulate and manage the extraction and trades. Blockchain technology provides a distributed concurrency monitoring system for sustainable resource management. Persistent and pervasive cooperation …

Presenting To Senior Decision Makers: Clear, Concise & Complete, Kirk Michealson

Operations Management Presentations

Your manager just assigned you to lead a new project for your Vice President. You have many questions! What are the details of the project? What does the VP want to see in briefings? Does the VP have an advocate for pre-briefs? What information is important to include in the presentation? How detailed should the information be? How should the information be presented? Are there any best practices in developing presentations? In this webinar, you will learn strategies for sharing important information with key stakeholders in your career – and how to actually get them to listen!

Design Of A Distributed Real-Time E-Health Cyber Ecosystem With Collective Actions: Diagnosis, Dynamic Queueing, And Decision Making, Yanlin Zhou

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

In this thesis, we develop a framework for E-health Cyber Ecosystems, and look into different involved actors. The three interested parties in the ecosystem including patients, doctors, and healthcare providers are discussed in 3 different phases. In Phase 1, machine-learning based modeling and simulation analysis is performed to remotely predict a patient's risk level of having heart diseases in real time. In Phase 2, an online dynamic queueing model is devised to pair doctors with patients having high risk levels (diagnosed in Phase 1) to confirm the risk, and provide help. In Phase 3, a decision making paradigm is proposed …

Experimental Designs, Meta-Modeling, And Meta-Learning For Mixed-Factor Systems With Large Decision Spaces, Zachary C. Little

Theses and Dissertations

Many Air Force studies require a design and analysis process that can accommodate for the computational challenges associated with complex systems, simulations, and real-world decisions. For systems with large decision spaces and a mixture of continuous, discrete, and categorical factors, nearly orthogonal-and-balanced (NOAB) designs can be used as efficient, representative subsets of all possible design points for system evaluation, where meta-models are then fitted to act as surrogates to system outputs. The mixed-integer linear programming (MILP) formulations used to construct first-order NOAB designs are extended to solve for low correlation between second-order model terms (i.e., two-way interactions and quadratics). The …

Diversity Team Building: Impact On Virtual Team Performance, Nina C. Magpili-Smith

Engineering Management & Systems Engineering Theses & Dissertations

Although organizations have addressed diversity issues at the organizational-level with resulting positive employee outcomes, lack of scholarly attention to team-level interventions remain. Team-level interventions would benefit organizations more directly as they address issues directly related to task accomplishment. Since diversity may lead to negative performance results for teams, a team building intervention based on the latest empirical research was developed and tested to address the potential performance losses associated to diversity in decision-making teams. The team building intervention provides six crucial elements, namely (1) direct experience of how deep-level team diversity affect team dynamics, (2) diversity education, (3) cultivation of …

Impact Of A Localized Lean Six Sigma Implementation On Overall Patient Safety And Process Efficiency, Luvianca Gil, Pilar Pazos, Mamadou Seck, Rolando Delaguila

Engineering Management & Systems Engineering Faculty Publications

Continuous quality improvement tools have caught the attention of the Health Care Industry as a solution to process efficiency, patient safety and cost reduction. This research explores the impact of a Lean Six Sigma (LSS) process improvement initiative in overall process efficiency and patient safety in two Labor and Delivery (L+D) units of two large hospital providers. This study focuses on the application of modeling and simulation methodology to investigate the influence of a localized process improvement intervention on the overall L+D unit output, by considering patient flow, system capacity and unit performance. The simulation models capacity profiles and patient …

Evaluating Forecasting Methods By Considering Different Accuracy Measures, Nijat Mehdiyev, David Lee Enke, Peter Fettke, Peter Loos

Engineering Management and Systems Engineering Faculty Research & Creative Works

Choosing the appropriate forecasting technique to employ is a challenging issue and requires a comprehensive analysis of empirical results. Recent research findings reveal that the performance evaluation of forecasting models depends on the accuracy measures adopted. Some methods indicate superior performance when error based metrics are used, while others perform better when precision values are adopted as accuracy measures. As scholars tend to use a smaller subset of accuracy metrics to assess the performance of forecasting models, there is a need for a concept of multiple accuracy dimensions to assure the robustness of evaluation. Therefore, the main purpose of this …

Understanding Risk Perception Using Fuzzy Cognitive Maps, Pei Zhang, Antoine J. Jetter

Engineering and Technology Management Faculty Publications and Presentations

When making decision that can have far-researching effects, such as governmental policies or decisions on new technologies, decision-makers use their understanding of the risks that are associated with their choices to guide their decisions. Measuring how people perceive risks can be helpful for understanding and possibly improving the decision-making process. Building on a review of existing methods for investigating risk perceptions, this paper suggests Fuzzy Cognitive Maps (FCM) as a method for investigating differences in risk perception among stakeholders and stakeholder groups. The approach is illustrated with an example of wildfire risk perceptions. Results suggest that FCM can contribute to …

Simultaneous Optimization And Sampling Of Agent Trajectories Over A Network, Hala Mostafa, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We study the problem of optimizing the trajectories of agents moving over a network given their preferences over which nodes to visit subject to operational constraints on the network. In our running example, a theme park manager optimizes which attractions to include in a day-pass to maximize the pass’s appeal to visitors while keeping operational costs within budget. The first challenge in this combinatorial optimization problem is that it involves quantities (expected visit frequencies of each attraction) that cannot be expressed analytically, for which we use the Sample Average Approximation. The second challenge is that while sampling is typically done …

Shortest Path Based Decision Making Using Probabilistic Inference, Akshat Kumar

Research Collection School Of Computing and Information Systems

We present a new perspective on the classical shortest path routing (SPR) problem in graphs. We show that the SPR problem can be recast to that of probabilistic inference in a mixture of simple Bayesian networks. Maximizing the likelihood in this mixture becomes equivalent to solving the SPR problem. We develop the well known Expectation-Maximization (EM) algorithm for the SPR problem that maximizes the likelihood, and show that it does not get stuck in a locally optimal solution. Using the same probabilistic framework, we then address an NP-Hard network design problem where the goal is to repair a network of …

The Effect Of Impeded Information Sharing And Transparency On Power Differentials And Organizational Dysfunction, Mustafa Canan, A. Sousa-Poza

Engineering Management & Systems Engineering Faculty Publications

The constituents of an organization have to interact with each other. The purpose of the interaction is to maintain flow of information, to exchange knowledge, to share individual situational awareness, and to give rise to an organizational shared awareness. The rate of information exchange is constrained by multiple factors and impacts the effectiveness of the communication in an organization. For instance, extensive communication may not result in informativeness all the time. Communication channels induce constraints between the interacting agents. These constraints can impede information flow. Impeding information flow will result in an accumulation of knowledge with a particular agent. Consequently, …

On Valuing Biopharmaceutical Product Pipelines: An Effectuation Model And Evidence, Mark J. Ahn, Anne S. York, Wei Wu, Yulianto Suharto, Tugrul Unsal Daim

Engineering and Technology Management Faculty Publications and Presentations

New creative approaches are needed to manage emerging biotechnology innovations, regulations, and payor environments to enhance product pipeline productivity, valuation, and risk management. Biopharmaceutical firms must make dynamic resource allocation decisions on their relative levels of internal R&D and external strategic alliances in furthering their pipelines. As the predominant method of using discounted cash flow (DCF) methodologies may lead to chronic underinvestment and performance, we evaluated the integration of traditional DCF with an effectuation model of analysis. Unlike traditional financial models that begin with the end goal of assumed known cash flows and recursively solve for portfolio optimization, the effectuation …

Assessing The Effectiveness Of Big Data Initiatives, Nayem Rahman, Fahad Aldhaban

Engineering and Technology Management Faculty Publications and Presentations

There is a great enthusiasm with the prospect of big data among business and industry leaders, academia and researchers. A lot of big data tools and technologies have emerged recently to capture, store, process and analyze big data. One remarkable achievement is that a handful of open source technologies have been introduced by Apache Hadoop Foundation that allows any organization to undertake big data projects. Many big data projects have been implemented during the last few years. This paper explores the benefits achieved with those projects. Big data has been applied in diverse fields including scientific and medical discovery projects, …

Explaining Health Technology Adoption: Past, Present, Future, Noshad Rahimi, Antonie J. Jetter

Engineering and Technology Management Faculty Publications and Presentations

One of the most pressing challenges of healthcare innovation today is the lack of technology adoption. Research that improves our ability to understand, predict, and advance technology adoption in health care needs to be based on well-tested theories. With the interest to conduct high quality research in health technology adoption in future, this study reviews the theories used in this context to either identify the superior theory(ies) and or discover the issues that need resolution for improving future HTA researches. To do that, the most popular [1][2] social cognitive theories conceived over the past four decades are reviewed analytically from …

Project Management In Product Development: Toward A Framework For Targeted Flexibility, Antonie J. Jetter, Fatima Albar

Engineering and Technology Management Faculty Publications and Presentations

As a discipline, project management has been accused of having lost its relevance for innovative initiatives because it emphasizes planning and control over the flexibility and learning-based strategies that are needed to succeed under uncertainty. Several authors therefore recommend adaptive project management practices - sometimes named “targeted flexibility” - that respond to project characteristics commonly found in innovation, namely novelty, complexity, speed and - as a result - uncertainty. This paper investigates how this proposed adaptation of project management occurs in a context with high levels of novelty that organizes work in projects and needs to accommodate projects of different …

Connecting Customers With Engineers For The Successful Fuzzy Front End: Requirements Of Tools, Byung Sung Yoon, Antonie J. Jetter

Engineering and Technology Management Faculty Publications and Presentations

In technology-driven enterprises, marketing typically acts as a “go-between” that captures customer needs and experiences and aggregates and interprets them for engineering. Knowledge exchange thus occurs through an indirect path. However, as a result of rapidly changing and unpredictable environments and complex products with tacit requirements, companies increasingly emphasize the need for engineering to be more strongly engaged with customers'. Accordingly, an increasing number of methods for customer research in early stages on new product development, the so-called fuzzy front end (FFE), emphasize direct knowledge exchange and collaboration between engineering and customers. Based on a review of the literature, this …

Project Ranking Using Partial Ranks, Jiali Ju, Pei Zhang, Tim R. Anderson

Engineering and Technology Management Faculty Publications and Presentations

A competition was recently held for new elder care technologies and a method was needed for selecting an audience favorite project. Since each of the eight projects received a half hour presentation time slot spread out over a full day, attendance varied significantly with morning projects having a much lower attendance. An algorithm was desired that was robust with respect to varying evaluator. A new algorithm for aggregating ranks from a large number of incomplete judgment was developed and applied to the projects to select a winner. This paper presents the new algorithm, tests the new approach against others in …

A Framework To Simplify The Choice Of Alternative Analysis And Selection Methods, James Paul Lewis Holzgrefe

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation contributes a framework for analysts and engineering managers to investigate and choose alternative analysis and selection methods based upon their problem and its context. It began as an investigation into the alternative analysis and selection methods used in military planning. The existing military methods were inconsistent, violated the decision science body of knowledge, and provided no guidance to the practitioner on matching methods to problems. These challenges made it necessary to conduct this investigation.

This research used a three-phase mixed methods approach. The first phase applied the general inductive method to the decision making body of knowledge to …