Operational Research Commons^™

Improve Outcomes In Lean Six Sigma With Servant Leadership, David W. Hoffa, Chad Laux, Manal Alduraibi

International Conference on Lean Six Sigma

1. Purpose

The purpose of this study was to explore lean leadership within Lean Six Sigma (LSS). The objective of this paper was to explore how LSS program success might be improved by focusing Black Belt efforts on mentoring Green Belts with a servant leadership model. The importance of Green Belt projects is typically overlooked in the literature. The effects of prioritizing the development of Green Belts and building a culture of continuous improvement over the traditional Black Belt project focus is explored.

2. Design/Methodology/Approach

The methodology of this paper is inspired by the authors’ field experiences in managing LSS …

Lean Six Sigma As An Enabler For Healthcare Operational Excellence In Covid-19, Olivia Mcdermott Dr, Antony Jiju

International Conference on Lean Six Sigma

1. Purpose -This paper aims to present the results of a qualitative research interview study on the utilization and importance of Lean Six Sigma methods in the Healthcare sector in COVID-19 and in pandemics in general.
2. Design/methodology/approach -a qualitative interview approach was utilised by interviewing leading Lean Six Sigma academics and practitioners who are expert in and have experience in Lean Six Sigma.
3. Findings – Lean Six Sigma methods are proven and can be utilised in pandemic situations to improve efficiency and resilience in the healthcare system and readiness for pandemics.
4. Research limitations/implications - One limitation of this research was that …

The Revenue Operations (Revops) Framework: A Qualitative Study Of Industry Practitioners., Oliviero Mottola

Dissertations and Theses

In recent years Revenue Operations or RevOps has emerged in professional circles as a new approach to manage Sales, Marketing and Customer Success teams in the context of b2b sales. In practitioner circles, RevOps definitions range from the increased collaboration of the three job functions to an all-out creation of job function within organizations. While the subject of interdepartmental alignment has been covered extensively in academia (albeit not exhaustively), RevOps as a term and set of practices has received no attention and industry practitioners struggle to find a unified set of best practices that isn’t coming from organizations trying to …

Modeling And Solving The Outsourcing Risk Management Problem In Multi-Echelon Supply Chains, Arian A. Nahangi

Master's Theses

Worldwide globalization has made supply chains more vulnerable to risk factors, increasing the associated costs of outsourcing goods. Outsourcing is highly beneficial for any company that values building upon its core competencies, but the emergence of the COVID-19 pandemic and other crises have exposed significant vulnerabilities within supply chains. These disruptions forced a shift in the production of goods from outsourcing to domestic methods.

This paper considers a multi-echelon supply chain model with global and domestic raw material suppliers, manufacturing plants, warehouses, and markets. All levels within the supply chain network are evaluated from a holistic perspective, calculating a total …

Developing A Basic Formal Supply Chain Ontology To Improve Communication And Interoperability, David Morrow

Theses and Dissertations

Information is crucial to supply chain performance because it is used to make decisions and trigger actions. Organizations across world-class supply chains increasingly use information technology to analyze and process supply chain data. However, supply chain management lacks a common language, making information exchange difficult. An ontology can provide a standardized framework that organizes a given knowledge domain. This research proposes a common language for developing a supply chain ontology that can be built into a basic formal ontology understood by both humans and computers. According to current research, an established and widely used supply chain framework is a good …

Strategies For Achieving The United States Health System's Quadruple Aim By Enhancing The Primary Care Level, Jennifer L. Mendoza-Alonzo

USF Tampa Graduate Theses and Dissertations

The quadruple aim is an approach to optimize the performance of the health system in the United States and consists of four dimensions. The main objective is to improve the population's health, followed by reducing cost, improving patients' experience, and increasing providers' satisfaction. In the present doctoral dissertation, I explore three strategies that help accomplish the quadruple aim at the primary care level. The analysis combines data science and operation research principles to address health system engineering questions.

Each strategy proposed in this document emphasizes one objective more than another; however, all of them in conjunction serve to attain the …

Integration Of Blockchain Technology Into Supply Network For Resilient And Efficient Acquisition [Video], Adrian Gheorghe, Farinaz Sabz Ali Pour, Unal Tatar, Omer Faruk Keskin, Cornel Vintila, Laura Manciu

Engineering Management & Systems Engineering Faculty Publications

In the modern acquisition, it is unrealistic to consider single entities as producing and delivering a product independently. Acquisitions usually take place through supply networks. Resiliency, efficiency, and effectiveness of supply networks directly contribute to the acquisition system's resiliency, efficiency, and effectiveness. All the involved firms form a part of a supply network essential to producing the product or service. The decision-makers have to look for new methodologies for supply chain management. Blockchain technology introduces new methods of decentralization and delegation of services, which can transform supply chains and result in a more resilient, efficient, and effective supply chain. This …

Multilayer Perceptron With Auto Encoder Enabled Deep Learning Model For Recommender Systems, Subhashini Narayan

Future Computing and Informatics Journal

In this modern world of ever-increasing one-click purchases, movie bookings, music, health- care, fashion, the need for recommendations have increased the more. Google, Netflix, Spotify, Amazon and other tech giants use recommendations to customize and tailor their search engines to suit the user’s interests. Many of the existing systems are based on older algorithms which although have decent accuracies, require large training and testing datasets and with the emergence of deep learning, the accuracy of algorithms has further improved, and error rates have reduced due to the use of multiple layers. The need for large datasets has declined as well. …

Toppings Refinery Retrofit, Connor Meyer Gulledge

Honors Capstone Projects and Theses

No abstract provided.

Robust Optimization With Recourse In Portfolio Management: Theory And Applications To Stocks And Projects, Hedieh Ashrafi, Aurelie Thiele

Operations Research and Engineering Management Theses and Dissertations

Many real-world decision problems in engineering and management have uncertain parameters. Robust optimization methodology takes into account the uncertainty in parameters of the model in the decision-making framework. In robust optimization methodology, we assume we do not know the probability distribution of parameters, and we have partial information about parameters. Portfolio management is one of those famous applications that have an uncertain environment. So, for this application, robust methodology would be a good choice. This dissertation contains three main works as the following:\\ In the first work, we provided the combination of European options and a robust optimization model to …

An Examination Of Grid Stability As It Relates To The Increased Integration Of Inverter-Based Resources, Daniel Voss

Electrical Engineering Undergraduate Honors Theses

There is currently a growing interest in increasing the amount of renewable energy resources connected to the bulk electric system (BES) that stems from various environmental, political, and social concerns. However, the differences between conventional generation resources and inverter-based resources (IBR)—namely wind and solar—pose new issues that make this increased integration a larger problem. In other studies, the increased penetration of renewable energy resources has resulted in weak-grid systems that are more susceptible to collapse. This comes as a result from the inability for IBRs to effectively provide enough reactive power, an effect especially apparent during fault conditions, which the …

Optimization With Interval Data: New Problems, Algorithms, And Applications., Mohsen Mohammadi Dehcheshmeh

Electronic Theses and Dissertations

The parameters of real-world optimization problems are often uncertain due to the failure of exact estimation of data entries. Throughout the years, several approaches have been developed to cope with uncertainty in the input parameters of optimization problems, such as robust optimization, stochastic optimization, fuzzy programming, parametric programming, and interval optimization. Each of these approaches tackles the uncertainty in the input data with different assumptions on the source of uncertainty and imposes different requirements on the returned solutions. In this dissertation, the approach we take is that of interval optimization, and more specifically, interval linear programming. The two main problems …

Locating Drone Battery Supply Stations To Facilitate The Delivery Of Medical Supplies In Low And Middle-Income Countries, Madeline Suellentrop

Industrial Engineering Undergraduate Honors Theses

In the sub-Saharan region of Africa, the inability to perform emergency blood transfusions due to an inadequate blood supply has led to high fatality rates, especially among women and children. The prevalence of disease in this region limits the supply of local blood donations and, if blood is imported, then the region’s poor infrastructure inhibits fast distribution. There is a need for a technological update in the current process that overcomes the limitations of regional transportation, and drones present one promising solution for delivering small, lightweight items such as blood units. The current focus of this new delivery method is …

Regression Analysis Of Pacing When Running A Marathon, Hawkin Starke

Industrial Engineering Undergraduate Honors Theses

Regression analysis can be an effective way of examining performance in the marathon event. By splitting up the race into segments or in runner terminology “splits” the significance of each segment as it relates to the total finish time can be explored. Because the idea of splits is already ingrained into the minds of runners, it makes intuitive sense to use these as the metrics to define a race. Additionally, marathons generally make participant age and gender date publicly available which can then be used to find trends within specific demographics. This tailors trends to smaller groups of people, making …

Noise Control In Sorting Conveyors, Eyra Herrera

Mechanical Engineering Undergraduate Honors Theses

E-commerce has increased the necessity of effective material handling equipment in warehouses and distribution centers. Sorter conveyors systems facilitate material handling by providing a reliable and automated system to classify and distribute products in a gentle and rapid manner. With the steady increase of speed in sorter conveyors to satisfy today’s industry demand, some systems have started to produce high noise levels that could potentially affect workers’ health. Since decreasing the speed of these conveyors is not a viable option to decrease noise in sorter equipment, industries have opted to find other ways to apply noise control to their equipment. …

Optimizing Garbage Pick-Up In Wahoo, Ne, Andrew Pace

Theses/Capstones/Creative Projects

This project seeks to optimize the garbage pickup routes of Roadrunner Transportation in Wahoo, Nebraska using operations research and optimization tools. Currently, the company has no formal procedure for determining these routes. Roadrunner Transportation would like to expand their operation and to do so in the most efficient manner. To determine efficient routes, the Capacitated Vehicle Routing Problem (CVRP) is applied, and a solution to this problem is obtained by implementing a simulated annealing heuristic algorithm. Results show that a total distance of approximately 70 miles can be obtained by this implementation using a small subset of the data provided …

Heuristics For Capacity Allocation And Queue Assignment In Congested Service Systems With Stochastic Customer Demand And Immobile Servers, Adam Colley

Operations Research and Engineering Management

We propose easy-to-implement heuristics for a problem referred to in the literature as the facility location problem with immobile servers, stochastic demand, and congestion, or the service system design problem. The problem is typically posed as one of allocating capacity to a set of M/M/1 queues to which customers with stochastic demand are assigned with the objective of minimizing a cost function composed of a fixed capacity-acquisition cost, a variable customer-assignment cost, and an expected-waiting-time cost. The expected-waiting-time cost results in a non-linear term in the objective function of the standard binary programming formulation of the problem. Thus, the solution …

Cost Functions Of Crabs: Applications Of Hermit Crab Shell Exchange Behavior To Vacancy Chain Modelling, Hannah Miele

Senior Honors Theses

Vacancy chain systems function as a method of resource distribution in domains such as housing and labor markets. Hermit crabs also employ vacancy chains as a method of shell exchange. Application of vacancy chain modelling in engineering has been attempted, but numerous flaws exist in the developed vacancy chain scheduling algorithm. This work addresses the lack of an appropriate vacancy chain cost function by developing a generalizable cost function based on hermit crab shell exchange behavior. The cost function’s purpose is enabling development of realistic engineering experiments and models based on real-world vacancy chain systems.

A Behavioral Model For Simultaneous Event Execution In Sequential Discrete Event System Simulations, Brian David S. Dilinila

Computational Modeling & Simulation Engineering Theses & Dissertations

The sequential execution of simultaneous events in a discrete event system simulation can cause unexpected behavior in a system. Current studies have provided approaches such as applying a priority order for simultaneous events. However, this is still a problem because executing simultaneous events in sequential order can still lead to two issues of simultaneous event conflicts: the case where simultaneous events cause changes to state variables required by other simultaneous events and the case where two or more simultaneous events cause changes to the same state variables. The objective of this thesis is to develop a behavioral model as a …

A Dynamic Programming Approach To Determine Optimum Modularity Level In Industrial Packaging, Marshal Louie, Kumar B

Journal of Applied Packaging Research

Modular packaging facilitate customization for accommodating variable product sizes in a product family. When determining package sizes for product variability, packaging engineers does not find difficulty to determine package dimension for less product variety whereas if the product variety is more, then determining the dimension of modular package involves complex decision-making and time-consuming process to find the optimal solution. This in turn directly impacts the overall lead time of the supply chain. Thus, in this paper a dynamic programming is developed to determine the quantity and dimension of modular packages for every demand of assorted products sizes. The program helps …

Strategic Upgrade Scheduling And Portfolio Management To Fortify Contested Networks, Justin L. Anderson

Theses and Dissertations

The nuclear command, control, and communication (NC3) network provides an effective deterrent against adversaries by maintaining robust communication between assets, operators, and decision makers. NC3 must receive a series of upgrades to remain an effective deterrent against evolving threats around the globe. Given a contested network and a portfolio of network upgrades, this research seeks an optimal upgrade schedule to maximize network resilience in support of NC3 modernization. Our research contributes a model that solves a budget-constrained network upgrade scheduling problem (NUSP). The NUSP is a defender-attacker-defender tri-level optimization model that achieves fortification via selecting and scheduling network upgrades. The …

Predicting F-16 Cause Code H Micap Hours Using Jmp Regression Analysis, Scott E. Carr

Theses and Dissertations

Emergency demands for aircraft parts, MICAPs (Mission Impaired Capability Awaiting Parts) are one of the leading issues affecting mission capability supply rates for fighter aircraft. Cause code H MICAPS, those with a known demand level, but no supply available, are particularly troublesome and difficult to resolve. These MICAPS are due to failures by the supply chain to replenish stock levels within acceptable time limits. Numerous studies have identified a clear need for proactive measures to reduce MICAP hours. This would significantly improve aircraft availability. This study uses regression analysis implemented in JMP software to build models with a goal of …

Air Combat Maneuvering Via Operations Research And Artificial Intelligence Methods, James B. Crumpacker

Theses and Dissertations

Within visual range air combat requires rapid, sequential decision-making to survive and defeat the adversary. Fighter pilots spend years perfecting maneuvers for these types of engagements, yet the emergence of unmanned, autonomous vehicle technologies elicits a natural question - can an autonomous unmanned combat aerial vehicle (AUCAV) be imbued with the necessary artificial intelligence to perform air combat maneuvering tasks independently? We formulate and solve the air combat maneuvering problem to examine this question, developing a Markov decision process model to control an AUCAV seeking to destroy a maneuvering adversarial vehicle. An approximate dynamic programming (ADP) approach implementing neural network …

Exploring The Limits Of Strategic Thought: Evaluating How Different Communication Modalities Affect The Nature Of Strategic Decision-Making Using Cognitive Hierarchy, Stephen D. Donnel

Theses and Dissertations

This research examines and quantifies the degree to which both information communication modality and the situational complexity affect individuals' ability to process the provided information and determine an effective strategy. Human subject testing herein consists of benign benevolent intervention involving the presentation of a series of strategic situations. For each situation, a participant attempts to identify their best response for a two-player, normal-form game with complete information. In each such game, players seek to maximize their own utility while considering their own actions, their opponent's actions, and each player's respective preferences over outcomes resulting from the possible combinations of actions. …

An Examination Of Potential Training Regression Recognition Algorithms For Pilot Training Next, Alex R. Gaines

Theses and Dissertations

The initiative to reduce the Air Forces serious pilot shortage lead to the Pilot Training Next (PTN) program. Under PTN, student pilots progress at an individual rate while making increased use of simulator-based training resources. A previous thesis used data from the first PTN class to conceptualize and prototype a student training flight scheduler. This scheduler did not consider training events required to bring students back to achieved levels of performance if in fact that student performance had regressed. This thesis examines three classes of PTN student data to determine whether student regression in training progression can be detected. A …

The Impact Of Triage Classification Errors On Military Medical Evacuation System Performance, Emily S. Graves

Theses and Dissertations

In a deployed environment, evacuation requests of injured personnel are serviced by multiple forms of evacuation including medical evacuation (MEDEVAC) and casualty evacuation (CASEVAC). This thesis focuses on the optimal dispatching policy for MEDEVAC units when triage classification errors and blood transfusion kits are considered. A discounted, infinite-horizon Markov decision process (MDP) model is formulated to analyze the MEDEVAC dispatching problem and determine the optimal policy based on the status of the MEDEVAC units in the system, the priority level of incoming requests, and the locations from which requests originate. A notional, representational scenario based in Azerbaijan is utilized to …

Allocation Of Scarce Healthcare Resources In A Military Treatment Facility During A Pandemic: A Comparison Of Goal Programming And Portfolio Decision Analysis Methods, Donald B. Hale

Theses and Dissertations

In a pandemic, healthcare decisionmakers face the challenge of allocating critical, but scarce healthcare resources in a dynamic, uncertain environment. Their decisions will not only affect the patients coming to the hospital for treatment, but also the Military Treatment Facility's personnel responsible. The decisionmaker must decide how to allocate these resources to achieve multiple, conflicting objectives under multiple constraints. In response, we propose a methodology for the implementation of both Portfolio Decision Analysis and Goal Programming. The steps of this methodology provide a framework with which the decisionmaker can develop optimal allocation of resources. This framework was then applied to …

Improving Air Battle Management Target Assignment Processes Via Approximate Dynamic Programming, Joseph M. Liles Iv

Theses and Dissertations

Military air battle managers face many challenges when directing operations in quickly evolving combat scenarios. These scenarios require rapid decisions to engage moving and unpredictable targets. In defensive operations, the success of a sequence of air battle management decisions is reflected by the friendly force's ability to maintain air superiority by defending friendly assets. We develop a Markov decision process (MDP) model of the air battle management (ABM)problem, wherein a set of unmanned combat aerial vehicles (UCAV) is tasked to defend a central asset from cruise missiles that arrive stochastically over time.

Examining Crucial Demographic Trends In General Aviation, Joshua D. Meyer

Theses and Dissertations

America's General Aviation sector has witnessed significant demographic shifts since the turn of the century. The number of certified, private pilots, non-fatal aircraft accidents, fatal aircraft accidents, and number of general aviation hours flown are all in decline. Meanwhile, the average age of an American private pilot has increased by several years. All of these factors indicate that the industry is in decline. This study determined via mathematical, linear regression that times relationship to the number of annual, fatal General Aviation accidents and the number of certified private pilots is negative. It also proved that the average age of the …

Resupply Operations Of A Dispersed Infantry Brigade Combat Team Using Approximate Dynamic Programming, Camero K. Song

Theses and Dissertations

Military sustainment planners must consider the effective employment of Cargo Unmanned Aerial Vehicles (CUAVs) into resupply operations under austere threat conditions. Viewed as an inventory routing problem, the complexities of resupplying dislocated Forward Operating Bases (FOBs) under dangerous and dynamic conditions warrant additional features to the baseline problem. This research models a military stochastic inventory routing problem with multiple routing (MIL SIRP- MR) as a Markov decision process (MDP) model and provides high-quality policy solutions using a combination of approximate dynamic programming and ordinal optimization techniques.