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Articles 31 - 60 of 169

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Constraint Optimal Selection Techniques (Costs) For A Class Of Linear Programming Problems, Tai-Kuan Sung Dec 2021

Constraint Optimal Selection Techniques (Costs) For A Class Of Linear Programming Problems, Tai-Kuan Sung

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

This dissertation describes two classes of Constraint Optimal Selection Techniques (COSTs). An algorithm of each type is developed for solving nonnegative linear programming problems. In addition, geometric interpretations of these new algorithms are given, computational results for some large-scale problems are provided, and directions for future research are discussed.


A Systematic Stakeholder-Driven Framework For Empirical Characterization And Parameterization Of Human Agents For Agent-Based Modeling Of Older Adults' Transportation, Nilufer Oran Gibson Dec 2021

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 …


Machine Learning Framework For Nonlinear And Interaction Relationships Involving Categorical And Numerical Features, Shirish Mohan Rao Aug 2021

Machine Learning Framework For Nonlinear And Interaction Relationships Involving Categorical And Numerical Features, Shirish Mohan Rao

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Traditionally, physical scientific experiments have been conducted extensively to study and understand the behavior of a process or a system. With the advancement of computing technology in recent years, computer codes and algorithms are used as simulators to replicate behavior of a complex system. Such use of computers to study a system is termed as ‘computer experiments.’ The process involves selecting specific points or runs in the design space in order to maximize information about the system in minimal runs. These computer models are high dimensional and can take a long time to simulate. Metamodels (or surrogate models) built using …


Agent-Based Model Simulation For Police Deployment Decision-Making In Patrol Operations, Yasaman Ghasemi Aug 2021

Agent-Based Model Simulation For Police Deployment Decision-Making In Patrol Operations, Yasaman Ghasemi

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Police patrolling plays a key role in responding to 911 calls and reducing crimes. The effectiveness of patrol operations heavily depends on the deployment of police officers – e.g., the number of officers assigned to specific policing districts or beats. The complex nature of the policing system – dynamic and stochastic criminal behavior, compounded with limited policing resources, render current (traditional) police operations, which are often managed in a reactive and stationary manner – often makes it very challenging to manage and control. This study develops an agent-based simulation framework to address the dynamically changing environment in police operations and …


Shape-Based Time Series Mining For Process Monitoring And Anomaly Detection, Li Zhang Aug 2021

Shape-Based Time Series Mining For Process Monitoring And Anomaly Detection, Li Zhang

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Due to the rapid development of computing and sensing technology, Internet of Things (IoT)-enabled monitoring plays a crucial role for people suffering from cardiac problems. It is important to detect the abnormal ECG cycles during the cardiac monitoring for the early treatment. However, most existing methods focused on the full reading of time series, for the cycle-based time series, it is wasting time to read the whole time series while we can find the characteristic patterns instead. Characteristic patterns named shapelets are time series subsequences, which are explainable and discriminative features that can best classify time series. Shapelet-based classification that …


Using Empirical Data To Design And Validate Hybrid Simulation Models Of Human Behavior In Service Operations, Mohammed Farhan May 2021

Using Empirical Data To Design And Validate Hybrid Simulation Models Of Human Behavior In Service Operations, Mohammed Farhan

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

The purpose of this research is to examine how a change in a team member's role, team dynamics, and organizational policies impact an individual's motivation to engage in helping behavior, as well as the impact of helping behavior on service system operational performance. To analyze these behavioral dynamics in a dynamic setting, this research integrates empirical human behavioral data into a hybrid discrete-event and agent-based simulation model of service operations in a restaurant. The model was then validated using Metamorphic Testing (MT), an approach that has previously been used for verification of software. Recent research shows that MT can be …


Teenage Cyclists’ Perception Towards Autonomous Vehicles And Its Associated Traffic Infrastructures, Obiageli Lawrentia Ngwu May 2021

Teenage Cyclists’ Perception Towards Autonomous Vehicles And Its Associated Traffic Infrastructures, Obiageli Lawrentia Ngwu

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Background: Cycling is a cost-effective means of transportation. Many teenagers cycle to go to schools and ride in neighborhoods. Cyclists are more vulnerable to injuries and fatalities than motor vehicle drivers. With the implementation of autonomous vehicles (AVs), interactions between AVs and road-users are expected to be safer. It is most likely that current young people will be the ones to use these vehicles and interact with them. However, very few past studies have focused on cyclist-AV interaction, with little to no attention toward the teenage cyclist population. Objectives: This study is aimed at examining teenage cyclists’ perceptions of AVs …


Bidding Enabled Inventory Redistribution In A Retail Network, Hafsa Binte Mohsin May 2021

Bidding Enabled Inventory Redistribution In A Retail Network, Hafsa Binte Mohsin

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

This research aspires to develop a systematic approach to minimize the demand and supply gap of products and product expiration in a feasible way. Inventory replenishment policy, uncertain customer demand, and forecast inaccuracy are some of the reasons that create imbalanced stocks in the outlets. Lateral transshipment or redistribution, donation, and promotion have been discussed in the existing literature separately as ways to balance and utilize inventory. Redistribution needs to account for extra transportation costs due to stock transfer. Existing literature on redistribution fails to address products’ physical attributes, valuation of products as a function of time, and constraint on …


A Multi-Objective Model For Sustainable Perishable Food Distribution Considering The Impact Of Temperature On Vehicle Emissions And Product Shelf Life, Amin Gharehyakheh, Caroline C. Krejci, Jaime Cantu, K. Jamie Rogers Aug 2020

A Multi-Objective Model For Sustainable Perishable Food Distribution Considering The Impact Of Temperature On Vehicle Emissions And Product Shelf Life, Amin Gharehyakheh, Caroline C. Krejci, Jaime Cantu, K. Jamie Rogers

Industrial, Manufacturing, and Systems Engineering Faculty Publications - Archive

The food distribution process is responsible for significant quality loss in perishable products. However, preserving quality is costly and consumes a tremendous amount of energy. To tackle the challenge of minimizing transportation costs and CO2 emissions while also maximizing product freshness, a novel multi-objective model is proposed. The model integrates a vehicle routing problem with temperature, shelf life, and energy consumption prediction models, thereby enhancing its accuracy. Non-dominated sorting genetic algorithm II is adapted to solve the proposed model for the set of Solomon test data. The conflicting nature of these objectives and the sensitivity of the model to shelf …


A Biomechanical Approach To Investigate The Effects On The Lumbosacral Joint, Pelvis, And Knee Joint While Of Carrying Asymmetrical Loads, During Ground Walking., Tomal Das Aug 2020

A Biomechanical Approach To Investigate The Effects On The Lumbosacral Joint, Pelvis, And Knee Joint While Of Carrying Asymmetrical Loads, During Ground Walking., Tomal Das

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Spinal pain is reasonably considered among the expensive and impairing problems critically disturbing the health of individuals, especially the workforce, in industrially developed countries (Steele et al., 2003). The pain adversely affecting the lumbar region or pelvis is typically considered as low back pain. As per the National Institute of Neurological Disorder and Stroke, around 80 percent of grown-ups encounter spinal pain eventually in the course of their lifetime. The possible risk factors include age, fitness level, genetics, weight gain, occupational risk factors such as having a job that expects someone to do lifting, carrying, pushing, pulling, distorting the spinal …


A Two-Stage Stochastic Programming Model For Enhancing Seismic Resilience Of Water Pipe Networks, Azam Boskabadi Aug 2020

A Two-Stage Stochastic Programming Model For Enhancing Seismic Resilience Of Water Pipe Networks, Azam Boskabadi

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Earthquakes are sudden and inevitable disasters that can cause enormous losses and suffering, and having accessible water is critically important for earthquake victims. To address this challenge, utility managers do preventive procedures on water pipes periodically to withstand future earthquake damage. The existing seismic vulnerability models usually consider simple methods to find the pipes to rehabilitate with highest priority. In this research, we develop an optimization approach to determine which water pipes to rehabilitate subject to a limited budget to achieve highest network serviceability after a disaster. We propose a two-stage stochastic mixed integer nonlinear program (MINLP). The MINLP model …


A New Method To Estimate The Impact On The L5/Si Spinal Disc From Speed Lifting Of Unstable Loads, Asymmetrically, Suhaib Al-Lababidi Aug 2020

A New Method To Estimate The Impact On The L5/Si Spinal Disc From Speed Lifting Of Unstable Loads, Asymmetrically, Suhaib Al-Lababidi

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Background: The most significant causes of lower back injuries at work are probably from manual lifting activities. Lifting unstable loads pose a significant strain to the lower back and can cause debilitating lumbar spine injuries. The primary function of the vertebral column is to support the upper body. The L5/S1 disc junction located between the lumbar and the sacral regions of the vertebral column is the most critical joint in spine with respect to lifting strain. Because of its position and the amount of upper body weight it handles, it is particularly vulnerable to misalignment, wear and tear, and injury.Lifting …


A Comparative Assessment Of Co2 Emission Between Gasoline, Electric, And Hybrid Vehicles: A Well-To-Wheel Perspective Using Agent-Based Modeling, Mdmamunur Rahman Aug 2020

A Comparative Assessment Of Co2 Emission Between Gasoline, Electric, And Hybrid Vehicles: A Well-To-Wheel Perspective Using Agent-Based Modeling, Mdmamunur Rahman

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Road transports in the U.S. are almost entirely dependent on the consumption of fossil fuel. This high dependency on fossil fuel is significantly contributing to carbon dioxide (CO2) emission, one of the leading Green House Gases (GHGs) responsible for global warming. Electrification of passenger vehicles could be an effective strategy to curb GHG emissions. Though Electric Vehicles (EVs) have zero tailpipe emissions, the power required to charge EV batteries may not necessarily come from carbon-free power plants. In this study, for a comprehensive comparison between EV and Gasoline Vehicle (GV), we developed an agent-based simulation model for the entire energy …


An Urban Modelling Framework For Climate Resilience In Low-Resource Neighbourhoods, Ulrike Passe, Michael Dorneich, Caroline Krejci, Diba Malekpour Koupaei, Breanna Marmur, Linda Shenk, Jacklin Stonewall, Janette Thompson, Yuyu Zhou Jul 2020

An Urban Modelling Framework For Climate Resilience In Low-Resource Neighbourhoods, Ulrike Passe, Michael Dorneich, Caroline Krejci, Diba Malekpour Koupaei, Breanna Marmur, Linda Shenk, Jacklin Stonewall, Janette Thompson, Yuyu Zhou

Industrial, Manufacturing, and Systems Engineering Faculty Publications - Archive

Climate predictions indicate a strong likelihood of more frequent, intense heat events. Resource-vulnerable, low-income neighbourhood populations are likely to be strongly impacted by future climate change, especially with respect to an energy burden. In order to identify existing and new vulnerabilities to climate change, local authorities need to understand the dynamics of extreme heat events at the neighbourhood level, particularly to identify those people who are adversely affected. A new comprehensive framework is presented that integrates human and biophysical data: occupancy/behaviour, building energy use, future climate scenarios and near-building microclimate projections. The framework is used to create an urban energy …


Robust, Time-Critical, Evidence-Based Adaptive Data Fusion, Mohammad Amin Javadi May 2020

Robust, Time-Critical, Evidence-Based Adaptive Data Fusion, Mohammad Amin Javadi

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Sensors have become inevitable part of many studies and working areas ranging from navigation, transportation and medical applications. A sensor can help a user in a variety of situations including dangerous, inaccessible, time and money-consuming circumstances. Applying multiple sensors simultaneously allows for improving the accuracy of measurement estimates for system states. As an example, a part of this study uses a GPS sensor to increase the accuracy of the position estimation obtained by an IMU in an indoor environment. The same GPS device with position outputs can also be studied to provide a new measuring dimension such as velocity. This …


Some New Results On Statistical Information And Evidence, Maryam Moghimi May 2020

Some New Results On Statistical Information And Evidence, Maryam Moghimi

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

This dissertation represents an attempt to relate some fundamental statistical problems using the notions of information, entropy, and evidence.


Identifying And Addressing Improvement Opportunities In Primary Care Clinics, Mozhdeh Sadighi May 2020

Identifying And Addressing Improvement Opportunities In Primary Care Clinics, Mozhdeh Sadighi

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

ABSTRACT: The main aim of this dissertation is to study how unrecognized opportunities for improving efficiency of in-person patient visits in a primary care clinic can be identified and addressed. To fulfill this goal, the research is divided into three distinct but related sections. Section one, with the most holistic view, uses a combination of scientific and rigorous methods along two research paths and, as a result, explores two opportunities for improvement in the clinic. These opportunities are high patient waiting time and unbalanced workload. Sections two and three each focus on underlying conditions driving one of these two opportunities. …


Mathematical Modeling Approaches In Sustainable Food Supply Chains, Amin Gharehyakheh May 2020

Mathematical Modeling Approaches In Sustainable Food Supply Chains, Amin Gharehyakheh

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Access to high quality and safe food is vital for sustainable development in societies. Perishable foods lose a major portion of their quality after harvesting until the consumption point due to poor storage and distribution conditions. Thus, improvements in food supply chain operations are very critical in the sustainable development of society and the industry. The first part of this dissertation seeks to find a cost-effective and reliable tool to monitor the quality loss and implementation of the least shelf life first-out inventory management policy in food banks. Application of the Gompertz model and Arrhenius equation based on time-temperature data …


Wart Treatment Decision Support Using Support Vector Machine, Md. Mamunur Rahman, Yuan Zhou, Shouyi Wang, Jamie Rogers Feb 2020

Wart Treatment Decision Support Using Support Vector Machine, Md. Mamunur Rahman, Yuan Zhou, Shouyi Wang, Jamie Rogers

Industrial, Manufacturing, and Systems Engineering Student Research - Archive

Warts are noncancerous benign tumors caused by the Human Papilloma Virus (HPV). The success rates of cryotherapy and immunotherapy, two common treatment methods for cutaneous warts, are 44% and 72%, respectively. The treatment methods, therefore, fail to cure a significant percentage of the patients. This study aims to develop a reliable machine learning model to accurately predict the success of immunotherapy and cryotherapy for individual patients based on their demographic and clinical characteristics. We employed support vector machine (SVM) classifier utilizing a dataset of 180 patients who were suffering from various types of warts and received treatment either by immunotherapy …


Assessing The Impact Of Principal Component Analysis On Accurately Predicting Melanoma Diagnosis Applied On Different Classification Models, Juan Cristobal Olmedo Rivera Dec 2019

Assessing The Impact Of Principal Component Analysis On Accurately Predicting Melanoma Diagnosis Applied On Different Classification Models, Juan Cristobal Olmedo Rivera

Industrial, Manufacturing, and Systems Theses - Archive

With huge amounts of data at our disposal in the medical field, mathematical models are built to diagnose diseases. This study focuses on melanoma because it’s the type of skin cancer that accounts for most deaths, up to 7,230 in 2019 according to the American Cancer Society. The study focuses on the effectiveness on diagnosing melanoma and how Principal Component Analysis (PCA) impacts the performance of four models being assessed, which are: K Nearest Neighbor (KNN), Logistic Regression (LR), Support Vector Machines (SVM), and Artificial Neural Networks (ANN). Each model evaluates the melanoma dataset before and after performing the PCA …


Planning And Optimization Of A Stochastic Multi-Phase Multi- Criteria Multi-Echelon Humanitarian Logistics Network, A B M Mainul Bari Dec 2019

Planning And Optimization Of A Stochastic Multi-Phase Multi- Criteria Multi-Echelon Humanitarian Logistics Network, A B M Mainul Bari

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Disasters, may that be anthropogenic or natural, cause much havoc to vast area and population. Property and infrastructures get destroyed. People are often in need of urgent relief like dry foods and water to survive. In a country which is in the underdeveloped part of the world, relief and evacuation activities are usually carried out by local government run aid agencies. Most of the time, the local decision makers do the coordination or planning of these humanitarian activities largely based on either past experience or sometimes just pure hunch, which is neither efficient nor economic. Proper planning and coordination in …


Multivariate Time Series Pattern Recognition Using Machine Learning And Deep Learning Methods, Sai Abhishek Devar Dec 2019

Multivariate Time Series Pattern Recognition Using Machine Learning And Deep Learning Methods, Sai Abhishek Devar

Industrial, Manufacturing, and Systems Theses - Archive

In this research work, we have implemented machine learning & deep-learning algorithms on real-time multivariate time series datasets in the manufacturing & health care fields. The research work is organized in two case-studies. The case study-1 is about rare event classification in multivariate time series in a pulp and paper manufacturing industry, data was collected of multiple sensors at each stage of production line, the data contains a rare event of paper break that commonly occurs in the industry. For preprocessing we have implemented sliding window approach for calculating first order difference method to capture the variation in the data …


Mars Knot Positioning And Global Optimization, Xinglong Ju Aug 2019

Mars Knot Positioning And Global Optimization, Xinglong Ju

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Multivariate adaptive regression splines (MARS) is a statistical modeling approach with wide real-world applications. In the MARS model building process, knot positioning is a critical step that potentially affects the accuracy of the final MARS model. Identifying well-positioned knots entails assessing the quality of many knots in each model building iteration, which requires much computation efforts. By exploring the change in the residual sum of squares (RSS) within MARS, we find that local optima from previous iterations can be very close to those of the current iteration. In our approach, the prior change in RSS information is used to “warm …


Analyzing Collaboration In Food Assistance Networks Using Agent-Based Modeling, Joyita Mostafa Aug 2019

Analyzing Collaboration In Food Assistance Networks Using Agent-Based Modeling, Joyita Mostafa

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

To address the issue of food insecurity, many small independent agencies, known as food pantries, collect and distribute donated food to food-insecure clients. However, the supply of donated food varies significantly from week to week, leading to frequent mismatches in supply and demand. One approach to addressing this problem is to facilitate greater food pantry collaboration, such that they are able to balance supply and demand among themselves. However, their interpersonal relationships and the additional costs associated with transshipments can be a barrier to collaboration. The objective of this research is to use modeling to gain a better understanding of …


A Multi-Agent Demand Response Planning And Operational Optimization Framework, Alireza Fallahi Aug 2019

A Multi-Agent Demand Response Planning And Operational Optimization Framework, Alireza Fallahi

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

This research describes a real-time optimization model for multi-agent demand response (DR) from a Load Serving Entity (LSE) perspective. We formulate two infinite horizon stochastic optimization models; specifically, an LSE model and a dynamic pricing customer model. The objective of these models is to minimize long-term cost and discomfort penalty of the LSE and dynamic pricing customers. We solve a deterministic finite horizon linear program as an approximation of the suggested stochastic model and provide computational experiments. In stochastic programming (SP), a wait-and-see solution is at least as good as an optimal policy. On the other hand, a policy that …


Uncovering Underlying Features For State Transition Modeling, Ashkan Farahani Aug 2019

Uncovering Underlying Features For State Transition Modeling, Ashkan Farahani

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Modeling of a dynamic system is the representation of the interconnectivity of system state variables and their evolutionary trajectory over time. In this dissertation, the terminology “state transition modeling” refers to a situation when the system state transitions and its evolution is unknown and needs to be estimated. There are situations in many application settings where one does not simply observe the behavior of the system, but also has a desire to take action, intervene, and manipulate one or more system variables, and is interested in seeing the causal effect of the intervention. These interventions within a purely observational setting, …


Data Science Applications In Health An Social Care, Maryuri Ariela Quintero Dec 2018

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 …


A Dynamic Policing Simulation Framework, Khan Md Ariful Haque Dec 2018

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 Dec 2018

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 Dec 2018

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) …