Operations Research, Systems Engineering and Industrial Engineering Commons^™

Group Facilitation, Terry Bresnick

Operations Management Presentations

As a management consultant, over the course of more than 40 years, I have facilitated more than 1500 workshops, seminars, and decision conferences. But when I think back on the times I was a college professor at West Point in the 70s, I often found myself in a position where in addition to teaching, I had to bring together and integrate the needs of very diverse groups of people. Typically, there was time pressure, the stakes were high, and the objectives of the participants conflicted. As an assistant professor, I had no real decision-making authority, but I could help the …

Data-Enabled Computational Multiscale Method In Materials Science And Engineering, Shaoping Xiao, Amaury Lendasse, Renjie Hu

Engineering Management and Systems Engineering Faculty Research & Creative Works

In the Community of Computational Materials Science, One of the Challenges in Hierarchical Multiscale Modeling is Information-Passing from One Scale to Another, especially from the Molecular Model to the Continuum Model. a Machine-Learning-Enhanced Approach, Proposed in This Paper, Provides an Alternative Solution. in the Developed Hierarchical Multiscale Method, Molecular Dynamics Simulations in the Molecular Model Are Conducted First to Generate Datasets, Which Represents Physical Phenomena at the Nanoscale. the Datasets Are Then Used to Train Neural Networks for Failure Classification and Stress Regressions. Finally, the Well-Trained Learning Machines Are Implemented in the Continuum Model to Study the Mechanical Behaviors of …

Blood-Based Biomarkers For Predicting The Risk For Five-Year Incident Coronary Heart Disease In The Framingham Heart Study Via Machine Learning, Meeshanthini V. Dogan, Steven R.H. Beach, Ronald L. Simons, Amaury Lendasse, Brandan Penaluna, Robert A. Philibert

Engineering Management and Systems Engineering Faculty Research & Creative Works

An Improved Approach for Predicting the Risk for Incident Coronary Heart Disease (CHD) Could Lead to Substantial Improvements in Cardiovascular Health. Previously, We Have Shown that Genetic and Epigenetic Loci Could Predict CHD Status More Sensitively Than Conventional Risk Factors. Herein, We Examine Whether Similar Machine Learning Approaches Could Be Used to Develop a Similar Panel for Predicting Incident CHD. Training and Test Sets Consisted of 1180 and 524 Individuals, respectively. Data Mining Techniques Were Employed to Mine for Predictive Biosignatures in the Training Set. an Ensemble of Random Forest Models Consisting of Four Genetic and Four Epigenetic Loci Was …

Data Science Applications In Health An Social Care, Maryuri Ariela Quintero

Industrial, Manufacturing, and Systems Theses - Archive

Health and social care are areas of concern worldwide nowadays. Chronic diseases such as cancer and social problems such as tobacco consumption are leading risks of deaths in many countries, and preventive efforts are urgently needed to decrease the negative impact that those problems cause. Technology has made available an unprecedent amount of data in the health and social care fields, which scientists are using to achieve a better understanding of many problems that are a burden for the health and social systems globally. Although previous studies have provided approaches to analyze data, more efficient and accurate methods are needed …

Teen Driver System Modeling: A Tool For Policy Analysis, Celestin Missikpode, Corrine Peek-Asa, Daniel V. Mcgehee, James Torner, Wayne Wakeland, Robert Wallace

Complex Systems Faculty Publications and Presentations

Background: Motor vehicle crashes remain the leading cause of teen deaths in spite of preventive efforts. Prevention strategies could be advanced through new analytic approaches that allow us to better conceptualize the complex processes underlying teen crash risk. This may help policymakers design appropriate interventions and evaluate their impacts.

Methods: System Dynamics methodology was used as a new way of representing factors involved in the underlying process of teen crash risk. Systems dynamics modeling is relatively new to public health analytics and is a promising tool to examine relative influence of multiple interacting factors in predicting a health …

Midpoint And Endpoint Sustainability Assessment Of U.S. And China Manufacturing: A Comparative Mrio+Recipe Analysis, Mustafa Saber

Master's Theses

Manufacturing is among the most important industries for an economy, which creates value-added, fosters innovation, stimulates employment and economic growth. Therefore, manufacturing industries are crucial for a country’s sustainable development not only for economic reasons but also for social (.e.g. employment, tax, etc.) and environmental ones. Thus, manufacturing activities’ contribution to the economy is critically related with environmental and social impacts. Sustainable economic growth is essential and necessary for a country to provide all necessary goods and services to its growing population.

And, this is highly linke with the creation of new jobs and in this context, manufacturing jobs have …

Thermal Comfort In Heated-And-Ventilated-Only Warehouses, Christian Taber, Donald G. Colliver

Biosystems and Agricultural Engineering Faculty Publications

Building energy codes and standards contain minimum requirements that provide a path to energy efficient buildings and building systems. ASHRAE/IES Standard 90.1 and the International Energy Conservation Code (IECC) are the main national building code models in the United States. Both Standard 90.1 and the IECC are updated on three-year cycles with the goal of reducing building energy consumption.

Crude Oil Prices Forecasting: Time Series Vs. Svr Models, Xin James He

Journal of International Technology and Information Management

This research explores the weekly crude oil price data from U.S. Energy Information Administration over the time period 2009 - 2017 to test the forecasting accuracy by comparing time series models such as simple exponential smoothing (SES), moving average (MA), and autoregressive integrated moving average (ARIMA) against machine learning support vector regression (SVR) models. The main purpose of this research is to determine which model provides the best forecasting results for crude oil prices in light of the importance of crude oil price forecasting and its implications to the economy. While SVR is often considered the best forecasting model in …

Table Of Contents Jitim Vol 27 Issue 3, 2018

Journal of International Technology and Information Management

Table of Contents

A Dynamic Policing Simulation Framework, Khan Md Ariful Haque

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Crime is a serious problem to a society, and its costs are an economic burden. With the help of technology and developed tools, law enforcement agencies are making significant efforts to combat crime, so as to create a safer environment for society, both mentally and physically. The dynamic nature of crime and limited police resources often make their efforts challenging. Although there are numerous crime prediction models found in the policing literature, guidelines for policing strategies based on those models are still lacking. Towards addressing this gap, this dissertation constructs a dynamic policing simulation framework based on the concept of …

A Parametric Process-Based Cost Estimation Framework To Support Conceptual Product Family Design And Production, Zahra Banakar

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

In today’s globally competitive environment, production costs estimation is a challenging task. This competitive market has brought specific strategies in the manufacturing sector, such as introducing more new products into the market with lower prices. In order to have the most accurate production costs estimation, accurate production cost information in a useful and relevant form is needed. This study presents a cost estimation framework that integrates both activity and parametric cost estimation methods to increase the ease, accuracy, and speed of producing cost estimates for a family of products or services. There is a need for an integrated production cost …

A Dynamic Multiple Stage, Multiple Objective Optimization Model With An Application To A Wastewater Treatment System, Prashant Tarun

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Decision-making for complex dynamic systems involves multiple objectives. Various methods balance the tradeoffs of multiple objectives, the most popular being weighted-sum and constraint-based methods. Under convexity assumptions an optimal solution to the constraint-based problem can also be obtained by solving the weighted-sum problems, and all Pareto optimal solutions can be obtained by systematically varying the weights or constraint limits. The challenge is to generate meaningful weights or constraint limits that yield practical solutions. In this dissertation, we utilize the Analytic Hierarchy Process (AHP) and develop a methodology to generate weight vectors successively for a dynamic multiple stage, multiple objective (MSMO) …

Global Renewable And Nonrenewable Energy Use Impact Assessment Of U.S. Manufacturing: An Integrated Cradle-To-Gate Lca And Dea Approach, Bahadir Ezici

Master's Theses

In this thesis, U.S. manufacturing industries` global supply chain-linked energy use and economic output are investigated considering a total of 16 renewable and nonrenewable energy carriers. A multiregion input output (MRIO) framework is employed to conduct the global supply chain-linked energy use impact assessment. The study period was between 1995 and 2014 based on data availability. Thus, 20 MRIO models were developed. Each MRIO model consists of the 40 largest economies of the world and the rest of the world (ROW) as the 41st country. Each country’s economy was structured into 35 manufacturing and service industries based on the Worth …

Collaborative Robotic Path Planning For Industrial Spraying Operations On Complex Geometries, Steven Brown

Graduate Theses and Dissertations

Implementation of automated robotic solutions for complex tasks currently faces a few major hurdles. For instance, lack of effective sensing and task variability – especially in high-mix/low-volume processes – creates too much uncertainty to reliably hard-code a robotic work cell. Current collaborative frameworks generally focus on integrating the sensing required for a physically collaborative implementation. While this paradigm has proven effective for mitigating uncertainty by mixing human cognitive function and fine motor skills with robotic strength and repeatability, there are many instances where physical interaction is impractical but human reasoning and task knowledge is still needed. The proposed framework consists …

Classifying Interdependencies In The Food And Agriculture Critical Infrastructure Sector, John Doerpinghaus

Graduate Theses and Dissertations

This work classifies examples of infrastructure interdependencies found in the food and agriculture critical infrastructure sector. Interdependencies are identified through an examination of rice and poultry agriculture throughout the state of Arkansas. The subtleties of interdependence examples in the food and agriculture sector are inadequately captured by the well-studied interdependence classification taxonomies. Through 39 interviews, we develop an understanding of the subtle temporal, geographic, and productivity scales of interdependence in over 100 examples and present five new, distinct classifications of interdependence: (1) dynamic physical, (2) dynamic geographic, (3) deadline, (4) delay, and (5) human, economic, and natural resource interdependencies. An …

System Engineering Analysis Of Terraforming Mars With An Emphasis On Resource Importation Technology, Brandon Wong

LMU Theses and Dissertations

This project uses System Engineering principles to delve into the viability of different methods for Terraforming Mars, with a comparison between Paraterraforming, Terraforming and Bioforming. It will then examine one subsystem that will be integral to the terraforming process, which is the space infrastructure necessary to import enough gases to recreate Earth’s atmosphere on Mars. It will analyze the viability of Chemical Rockets, Nuclear Rockets, Space Elevators, Skyhooks, Rotovators, Mass Drivers, Launch Loops and Orbital Rings for this subsystem and provide recommendations for an implementation plan.

Data Center Holistic Demand Response Algorithm To Smooth Microgrid Tie-Line Power Fluctuation, Ting Yang, Yingjie Zhao, Haibo Pen, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

With the rapid development of cloud computing, artificial intelligence technologies and big data applications, data centers have become widely deployed. High density IT equipment in data centers consumes a lot of electrical power, and makes data center a hungry monster of energy consumption. To solve this problem, renewable energy is increasingly integrated into data center power provisioning systems. Compared to the traditional power supply methods, renewable energy has its unique characteristics, such as intermittency and randomness. When renewable energy supplies power to the data center industrial park, this kind of power supply not only has negative effects on the normal …

Budget-Constrained Regression Model Selection Using Mixed Integer Nonlinear Programming, Jingying Zhang

Graduate Theses and Dissertations

Regression analysis fits predictive models to data on a response variable and corresponding values for a set of explanatory variables. Often data on the explanatory variables come at a cost from commercial databases, so the available budget may limit which ones are used in the final model.

In this dissertation, two budget-constrained regression models are proposed for continuous and categorical variables respectively using Mixed Integer Nonlinear Programming (MINLP) to choose the explanatory variables to be included in solutions. First, we propose a budget-constrained linear regression model for continuous response variables. Properties such as solvability and global optimality of the proposed …

Credit Assignment For Collective Multiagent Rl With Global Rewards, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Scaling decision theoretic planning to large multiagent systems is challenging due to uncertainty and partial observability in the environment. We focus on a multiagent planning model subclass, relevant to urban settings, where agent interactions are dependent on their collective influence'' on each other, rather than their identities. Unlike previous work, we address a general setting where system reward is not decomposable among agents. We develop collective actor-critic RL approaches for this setting, and address the problem of multiagent credit assignment, and computing low variance policy gradient estimates that result in faster convergence to high quality solutions. We also develop difference …

Integrated Reward Scheme And Surge Pricing In A Ride-Sourcing Market, Hai Yang, Chaoyi Shao, Hai Wang, Jieping Ye

Research Collection School Of Computing and Information Systems

Surge pricing is commonly used in on-demand ride-sourcing platforms (e.g., Uber, Lyft and Didi) to dynamically balance demand and supply. However, since the price for ride service cannot be unlimited, there is usually a reasonable or legitimate range of prices in practice. Such a constrained surge pricing strategy fails to balance demand and supply in certain cases, e.g., even adopting the maximum allowed price cannot reduce the demand to an affordable level during peak hours. In addition, the practice of surge pricing is controversial and has stimulated long debate regarding its pros and cons. To address the limitation of current …

Design And Implementation Of Decision Support For Traffic Management At Multipurpose Port Gates, Ketki Kulkarni, Hoong Chuin Lau, Hai Wang, Sathyavarathan Sivabalasingam, Trong Khiem Tran

Research Collection School Of Computing and Information Systems

Effective traffic management can help port operators gain a competitive edge in service level and efficient use of limited resources. One critical aspect of traffic management is gate operations management, ensuring a good customer experience to logistic carriers and considering the impact of congestion in and around the port. In this paper, we describe the design and implementation of a decision support tool to help gate operators plan for future scenarios with fluctuating demand and limited resources. We propose a simulation optimization framework which incorporates theoretical results from queuing theory to approximate complex multi-lane multi-server systems. Our major contribution in …

Discrete Event Simulation And Cost Model For Optimization Of Manufacturing Resource Usages Associated With Implementation Of A Redesigned Product, Alexander Eierle

Theses and Dissertations

This paper demonstrates an approach to evaluating production factors related to schedule and resources based on changes to the production process. A discrete event simulation model was developed to evaluate different production factors, such as arrival times, number of entities, resource availabilities, and work in process (WIP) times, compared to the total yield at a production facility. This model helped to develop relationships between the required asset resource usages and the overall production resource allocation with the related effects to process wait times and production outputs. A comparative analysis with cost was performed to determine the effect that varied resources …

Real-Time Heuristics And Metaheuristics For Static And Dynamic Weapon Target Assignments, Alexander G. Kline

Theses and Dissertations

The problem of targeting and engaging individual missiles (targets) with an arsenal of interceptors (weapons) is known as the weapon target assignment problem. This problem has been well-researched since the seminal work in 1958. There are two distinct categories of the weapon target assignment problem: static and dynamic. The static weapon target assignment problem considers a single instance in which a known number of incoming missiles is to be engaged with a finite number of interceptors. By contrast, the dynamic weapon target assignment problem considers either follow on engagement(s) should the first engagement(s) fail, a subsequent salvo of incoming missiles, …

Introduction To Data Analytics And Emerging Real-World Use Cases, Art Chaovalitwongse

Operations Management Presentations

Data analytics is a rapidly emerging interdisciplinary research area that involves advances in engineering, computer science, statistics and operations research. This webinar is focused on introducing the foundation of data analytics and emerging real-world use cases of data analytics. This presentation will begin with a discussion of the mathematical and statistical modeling aspects of various levels of data analytics (i.e., descriptive, predictive and prescriptive). In this webinar, you will hear an overview of data analytics in real world problems ranging from healthcare analytics, retail analytics and financial analytics.

Smart Disease Prevention App: Informing The Public In Their Own Geographic Location, Apoorva Sulakhe, Shafali Rana, Zoe Disori, William Nogay, Kyle Plummer, Meredith Shannon, Morgan Young, Alyssa Zielinski, Vincent G. Duffy

Purdue Journal of Service-Learning and International Engagement

Apoorva Sulakhe and Shefali Rana are graduate students in the School of Industrial Engineering at Purdue. They have both been teaching assistants under their coauthor, Dr. Vincent Duffy, while supervising multiple projects. Coauthors Zoe Disori, William Nogay, Kyle Plummer, Meredith Shannon, Morgan Young, and Alyssa Zielinski are listed in alphabetical order. They were all seniors in School of Industrial Engineering at the time of this project in 2017. The purpose of their study, described in this article, was to develop an application to provide users with accurate information about diseases spreading in their geographic locations.

Cost Benefit Analysis Of Led Vs Florescent Lighting, Kurtis Clark, Phillip Humphrey

Student Research

Over the last few years, the state of Oklahoma has been looking at ways to reduce expenses to address concerns about a budget deficit. There have been efforts made to reduce expenses due to the use of energy. It has been said, when the lights are on, work is getting done. Running lights is therefore the cost of doing business. Our research examines the question, “is there a way to provide better lighting while operating at a lower cost.” This research examines the current lighting at Southwestern State University, primarily fluorescent lighting (FL), and a cost benefit analysis of switching …

Multi-Objective Evolutionary Neural Network To Predict Graduation Success At The United States Military Academy, Gene Lesinski, Steven Corns

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper presents an evolutionary neural network approach to classify student graduation status based upon selected academic, demographic, and other indicators. A pareto-based, multi-objective evolutionary algorithm utilizing the Strength Pareto Evolutionary Algorithm (SPEA2) fitness evaluation scheme simultaneously evolves connection weights and identifies the neural network topology using network complexity and classification accuracy as objective functions. A combined vector-matrix representation scheme and differential evolution recombination operators are employed. The model is trained, tested, and validated using 5100 student samples with data compiled from admissions records and institutional research databases. The inputs to the evolutionary neural network model are used to classify …

System Of Systems Architecting Problems: Definitions, Formulations, And Analysis, Hadi Farhangi, Dincer Konur

Engineering Management and Systems Engineering Faculty Research & Creative Works

The system of systems architecting has many applications in transportation, healthcare, and defense systems design. This study first presents a short review of system of systems definitions. We then focus on capability-based system of systems architecting. In particular, capability-based system of systems architecting problems with various settings, including system flexibility, fund allocation, operational restrictions, and system structures, are presented as Multi-Objective Nonlinear Integer Programming problems. Relevant solution methods to analyze these problems are also discussed.

Densenet For Anatomical Brain Segmentation, Ram Deepak Gottapu, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Automated segmentation in brain magnetic resonance image (MRI) plays an important role in the analysis of many diseases and conditions. In this paper, we present a new architecture to perform MR image brain segmentation (MRI) into a number of classes based on type of tissue. Recent work has shown that convolutional neural networks (DenseNet) can be substantially more accurate with less number of parameters if each layer in the network is connected with every other layer in a feed forward fashion. We embrace this idea and generate new architecture that can assign each pixel/voxel in an MR image of the …

Early Detection Of Disease Using Electronic Health Records And Fisher's Wishart Discriminant Analysis, Sijia Yang, Jian Bian, Zeyi Sun, Licheng Wang, Haojin Zhu, Haoyi Xiong, Yu Li

Engineering Management and Systems Engineering Faculty Research & Creative Works

Linear Discriminant Analysis (LDA) is a simple and effective technique for pattern classification, while it is also widely-used for early detection of diseases using Electronic Health Records (EHR) data. However, the performance of LDA for EHR data classification is frequently affected by two main factors: ill-posed estimation of LDA parameters (e.g., covariance matrix), and "linear inseparability" of the EHR data for classification. To handle these two issues, in this paper, we propose a novel classifier FWDA -- Fisher's Wishart Discriminant Analysis, which is developed as a faster and robust nonlinear classifier. Specifically, FWDA first surrogates the distribution of "potential" inverse …