Engineering Commons^™

Meal Duration: Implications For Restaurant Revenue Management, Dale F. Billings

UNLV Theses, Dissertations, Professional Papers, and Capstones

A comprehensive revenue management strategy addressing space, product, price and time, has been shown to increase profits within the hospitality sector. While the literature shows that the restaurant industry has frequently addressed space, product, and price when looking at financial strategy, the effect of the variable of time on revenue generation has not been adequately studied. Restaurants shy away from the practice of using time as a commodity, particularly regarding meal duration, due to fears of reducing customer satisfaction.

This project explores the use of time as a commodity in restaurant revenue management. In particular, it examines consumers’ feelings about ...

Artificial Bee Colony Algorithm For Solving Fuzzy Multi-Objective Bed Allocation Model, Abdulhakeem Luqman Hasan

Karbala International Journal of Modern Science

With the improvement of the medical services frameworks rivalry, hospitals face more and more challenges. In the interim, allotment of resource has a crucial influence on performing competitive benefits in a hospitals. To choose the suitable beds number is one of the most essential tasks in hospital administration. Anyway, in true condition, bed allotment choice is a multiple-side problem with weakness and haphazardness of the information available. It is so sophisticated. Therefore, the research about bed allotment difficulty is comparatively rare under considering multiple departments, nursing hours, and stochastic information about arrival and service of patients. In this paper, we ...

Uncertainty And Error In Combat Modeling, Simulation, And Analysis, Jason A. Blake

Theses and Dissertations

Due to the infrequent and competitive nature of combat, several challenges present themselves when developing a predictive simulation. First, there is limited data with which to validate such analysis tools. Secondly, there are many aspects of combat modeling that are highly uncertain and not knowable. This research develops a comprehensive set of techniques for the treatment of uncertainty and error in combat modeling and simulation analysis. First, Evidence Theory is demonstrated as a framework for representing epistemic uncertainty in combat modeling output. Next, a novel method for sensitivity analysis of uncertainty in Evidence Theory is developed. This sensitivity analysis method ...

Effects Of Musical Ability On Flight Planning, Situational Awareness, And Flight Path Deviations, Andrew P. Henry

PhD Dissertations and Master's Theses

Numerous studies have been conducted on music education and the benefits that learning an instrument has on the brain. However, there is little research that connects a pilot’s ability to play an instrument to a pilot’s ability to fly an airplane. When learning an instrument, students learn non-musical abilities, such as executive functions, which may correspond with the skills necessary to be a good pilot. The purpose of this study was to find a relationship between learning a musical instrument and pilot performance, specifically related to flight planning, situational awareness, and flight path deviations. This study was a ...

Resource Allocation And Task Scheduling Optimization In Cloud-Based Content Delivery Networks With Edge Computing, Yang Peng

Engineering Management, Information, and Systems Research Theses and Dissertations

The extensive growth in adoption of mobile devices pushes global Internet protocol (IP) traffic to grow and content delivery network (CDN) will carry 72 percent of total Internet traffic by 2022, up from 56 percent in 2017. In this praxis, Interconnected Cache Edge (ICE) based on different public cloud infrastructures with multiple edge computing sites is considered to help CDN service providers (SPs) to maximize their operational profit. The problem of resource allocation and performance optimization is studied in order to maximize the cache hit ratio with available CDN capacity.

The considered problem is formulated as a multi-stage stochastic linear ...

Extracting Patterns In Medical Claims Data For Predicting Opioid Overdose, Ryan Sanders

Theses and Dissertations

The goal of this project is to develop an efficient methodology for extracting features from time-dependent variables in transaction data. Transaction data is collected at varying time intervals making feature extraction more difficult. Unsupervised representational learning techniques are investigated, and the results compared with those from other feature engineering techniques. A successful methodology provides features that improve the accuracy of any machine learning technique. This methodology is then applied to insurance claims data in order to find features to predict whether a patient is at risk of overdosing on opioids. This data covers prescription, inpatient, and outpatient transactions. Features created ...

Optimizing Block-Stacking Operations With Relocation, Hueon Lee

Theses and Dissertations

The focus of the dissertation is developing the optimization problem of finding the minimum-cost operational plan of block stacking with relocation as well as devising a solution procedure to solve practical-sized instances of the problem. Assuming changeable row depth instead of permanent row depth, this research is distinguished from conventional block stacking studies.

The first contribution of the dissertation is the development of the optimization problem under the assumption of deterministic demand. The problem is modeled using integer programming as a variation of the unsplittable multi-commodity flow problem. To find a good feasible solution of practical-sized instances in reasonable time ...

Resource-Constrained Project Scheduling With Autonomous Learning Effects, Jordan M. Ticktin

Master's Theses

It's commonly assumed that experience leads to efficiency, yet this is largely unaccounted for in resource-constrained project scheduling. This thesis considers the idea that learning effects could allow selected activities to be completed within reduced time, if they're scheduled after activities where workers learn relevant skills. This paper computationally explores the effect of this autonomous, intra-project learning on optimal makespan and problem difficulty. A learning extension is proposed to the standard RCPSP scheduling problem. Multiple parameters are considered, including project size, learning frequency, and learning intensity. A test instance generator is developed to adapt the popular PSPLIB library ...

Rfid Item-Level Tagging In A Grocery Store Environment, Brian Truman

LSU Master's Theses

The purpose of this research was to investigate how effective item-level Radio Frequency Identification (RFID) tagging would be using current RFID technology as a replacement for barcodes in a supermarket/grocery store environment.

To accomplish this, an experiment was be performed that utilized commercially available RFID technology. Passive Ultra High Frequency (UHF) RFID Tags were affixed to various grocery store items of different material categories (Food, Metal, Plastic, Liquid, and Glass), and placed in a metal shopping cart. Eight (8) antenna arrangements were created, comprised of different combinations of four (4) antennas in different locations around the cart.

The experiment ...

Algorithms For Multi-Objective Mixed Integer Programming Problems, Alvaro Miguel Sierra Altamiranda

Graduate Theses and Dissertations

This thesis presents a total of 3 groups of contributions related to multi-objective optimization. The first group includes the development of a new algorithm and an open-source user-friendly package for optimization over the efficient set for bi-objective mixed integer linear programs. The second group includes an application of a special case of optimization over the efficient on conservation planning problems modeled with modern portfolio theory. Finally, the third group presents a machine learning framework to enhance criterion space search algorithms for multi-objective binary linear programming.

In the first group of contributions, this thesis presents the first (criterion space search) algorithm ...

Three Essays On Data-Driven Optimization For Scheduling In Manufacturing And Healthcare, Ekin Koker

Doctoral Dissertations

This dissertation consists of three essays on data-driven optimization for scheduling in manufacturing and healthcare. In Chapter 1, we briefly introduce the optimization problems tackled in these essays. The first of these essays deals with machine scheduling problems. In Chapter 2, we compare the effectiveness of direct positional variables against relative positional variables computationally in a variety of machine scheduling problems and we present our results. The second essay deals with a scheduling problem in healthcare: the team primary care practice. In Chapter 3, we build upon the two-stage stochastic integer programming model introduced by Alvarez Oh (2015) to solve ...

The Business Case For Industrial Safety: Revealing The Comprehensive Value Of Ergonomic Investments For Manufacturing Enterprises In Industry 4.0, Shane Stan

Honors Theses, University of Nebraska-Lincoln

How can today’s manufacturing enterprises construct, implement, and optimize modern safety initiatives in a manner that will present maximum return on investment and facilitate enterprise growth? Furthermore, how can these manufacturers assure individual ergonomic investments become part of a larger strategy to facilitate organizational change in safety? This work addresses these questions by placing industrial ergonomics in a business improvement context which comprehensively presents the financial returns and growth opportunities poised by modern safety initiatives. Additionally, to further strengthen the business case for industrial safety, an ergonomic action planning framework is established to guide the creation of holistic safety ...

Prioritizing Strategic Cyberspace Lethality, Andrew J. Schoka

Military Cyber Affairs

The primary concern of United States national security policy, as detailed in the 2018 National Defense Strategy, has shifted from asymmetrical counter-insurgency operations to countering inter-state strategic competition by rogue regimes and revisionist powers. This doctrinal shift has prompted an increased emphasis on military lethality, particularly in strategic-level cyberspace operations intended to counter open challenges to the global security environment and United States preeminence. Drawing from the theory of constraints in industrial engineering and Bayesian search theory in operations research, this paper identifies the key organizational constraints that hinder the lethality of the Department of Defense’s strategic-level cyberspace operations ...

A Comparison Of Multi-Attribute Utility Theory, The Analytic Hierarchy Process, The Analytic Network Process, And New Hybrid Approaches For A Case Study Involving Radon, Jesse Ray Toepfer

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation focuses on the use of three new combinational hybrid approaches to solve a rational decision problem. Even though Multi-Attribute Utility Theory (MAUT) and the Analytic Hierarchy Process (AHP), and the Analytic Network Process (ANP), are all long established theories, their practical applications continue to grow and generate new knowledge. As a case study approach, there exists a knowledge gap concerning the use of these MCDM methods in the area of environmental remediation, and more especially, in situations that involve radioactive materials. From this, and as borne out by the literature review discussed herein, a problem statement is thus ...

Paints-R-Us Term Project, Tyler Campbell, Skye Gilbreth, Michael Oluwole, Elijah Raffo, Brad Unruh

Engineering and Technology Management Student Projects

This project will consider a linear product mix optimization problem for a fictional paint company, Paints-R-Us. Paints-R-Us is a wholesale paint manufacturer located in the Pacific Northwest. The Global Production Manager, Steve Brush, has been tasked with maximizing Paints-R-Us’s profit in the upcoming quarter. Steve Brush oversees the global production plan, and in collaboration with the production planners will develop a production plan which optimizes the profits that Paints-R-Us can create in the quarter accounting for the following criteria:

• Demand in the given quarter for each of the 5 paint types that Paints-R-Us produces • The warehousing storage capacity for ...

Identifying And Quantifying Personnel Skills Gaps, Martin Joseph Mckenney

Engineering Management & Systems Engineering Theses & Dissertations

One of the issues organizations face is identifying the required skills needed for a position and then evaluating whether their personnel have these skills or if there is a “skills gap”. The skills gap is the distance between the position requirements and the skills currently possessed by the worker in that position. While multiple models have been created over the years to address facets of the problem, none of them provide a comprehensive framework to clearly identify the required skills and worker qualifications and then evaluate the degree of similarity. A composite skills gap model has been developed using the ...

The Impact Of Executing A Warehouse Management System Change: A Case Study, Nicholas J. Cross

Masters Theses & Specialist Projects

The increased demand on distribution centers to provide quicker turnarounds from receiving to shipping while maintaining precise inventory accuracies is spurring the acquisition of a warehouse management system (WMS) to improve operations and increase efficiency. With the rapid expansion of WMS technology, it seems inevitable that warehouses will outgrow inefficient operational processes and switch to a system that can accommodate rapid development. Research has explained the financial burdens and benefits of acquiring a WMS, but there’s been minimal research describing the impacts of the actual implementation. This study took place within a 600,000 sq. ft. fulfillment center and ...

Assessing Values-Based Sourcing Strategies In Regional Food Supply Networks: An Agent-Based Approach, Caroline C. Krejci, Michael C. Dorneich, Richard T. Stone

Richard T. Stone

The recent increase in demand for regionally produced food has resulted in a need for more efficient distribution methods. To connect regional food producers and consumers, intermediated regional food supply networks have developed. The intermediary, known as a regional food hub, serves as an aggregation point for products and information. It may also act as a filter to ensure that the requirements of both producers and consumers are consistently met. This paper describes an empirically based agent-based model of a regional food network in central Iowa that is intermediated by a food hub. The model was used to test a ...

Backhaul Profit Maximization Problem Instances, Yuanyuan Dong, Yulan Bai, Eli V. Olinick, Andrew Junfang Yu

Engineering Management, Information, and Systems Research

This archive contains data for the problem instances described in the technical report "An Empirical Study of Mixed Integer Programming Formulations of the Backhaul Profit Maximization Problem" by Yulan Bai and Eli V. Olinick.

An Empirical Study Of Mixed Integer Programming Formulations Of The Backhaul Profit Maximization Problem, Yulan Bai, Eli V. Olinick

Engineering Management, Information, and Systems Research

Solving an instance of the Backhaul Profit Maximization Problem (BPMP) requires simultaneously solving two problems: (1) determining how to route an empty delivery vehicle back from its current location to its depot by a scheduled arrival time, and (2) selecting a profit-maximizing subset of delivery requests between various locations on the route subject to the vehicle's capacity. We propose and test a series of enhancements to the node-arc and triples mixed integer programming formulations of BPMP found in the literature and develop a multi-criteria Composite Index Method (CIM) to evaluate the results. We find that CPLEX takes 5 to ...

Operational Decision Making Under Uncertainty: Inferential, Sequential, And Adversarial Approaches, Andrew J. Keith

Theses and Dissertations

Modern security threats are characterized by a stochastic, dynamic, partially observable, and ambiguous operational environment. This dissertation addresses such complex security threats using operations research techniques for decision making under uncertainty in operations planning, analysis, and assessment. First, this research develops a new method for robust queue inference with partially observable, stochastic arrival and departure times, motivated by cybersecurity and terrorism applications. In the dynamic setting, this work develops a new variant of Markov decision processes and an algorithm for robust information collection in dynamic, partially observable and ambiguous environments, with an application to a cybersecurity detection problem. In the ...

Extreme-Point Tabu Search Heuristics For Fixed-Charge Generalized Network Problems, Angelika Leskovskaya

Engineering Management, Information, and Systems Research Theses and Dissertations

While researchers have studied generalized network flow problems extensively, the powerful addition of fixed charges on arcs has received scant attention. This work describes network-simplex-based algorithms that efficiently exploit the quasi-tree basis structure of the problem relaxations, proposes heuristics that utilize a candidate list, a tabu search with short and intermediate term memories to do the local search, a diversification approach to solve fixed-charge transportation problems, as well as a dynamic linearization of objective function extension for the transshipment fixed-charge generalized problems. Computational testings for both heuristics demonstrate their effectiveness in terms of speed and quality of solutions to these ...

Design Thinking: An Approach With Various Perceptions, Sanne Bouwman, Jesper Voorendt, Boris Eisenbart, Seda Mckilligan

Industrial Design Conference Presentations, Posters and Proceedings

Design Thinking has become increasingly popular across different disciplines. However, what it exactly entails is becoming more and more vague, leading to the term being used for many different approaches and applications. This paper presents an interview study with experts on the application and training of Design Thinking in academia and industry. We find a divide with some seeing Design Thinking as a mere toolbox of methods, while others see it as an umbrella term for the mindset that determines how designers think and act. Subjects unanimously attest the approach large potential to support certain types of businesses, when applied ...

Equilibrium Modeling And Policy Analysis Of A Biofuel Supply Chain With A Hydroelectric Reservoir, Jinwoo Bae

Theses and Dissertations

This research proposesd a game theoretic model of a biofuel supply chain (BSC) where a utility company supplies reservoir water to two farmers, located in downstream and upstream of a hydropower dam. The decision-making process of the model is formulated as a three-stage Stackelberg game. We analyze the equilibrium of the decentralized systems and the effect of the government subsidy on energy crop (switchgrass) production for cellulosic biofuel industries, with two forms of subsidy: (1) discriminated subsidies and (2) equalized subsidies.

The results show that both forms of subsidy improve social welfare in the BSC unless the amount of subsidy ...

Probabilistic Models For Order-Picking Operations With Multiple In-The-Aisle Pick Positions, Jingming Liu

Theses and Dissertations

The development of probability density functions (pdfs) for travel time of a narrow aisle lift truck (NALT) and an automated storage and retrieval (AS/R) machine is the focus of the dissertation. The multiple in-the-aisle pick positions (MIAPP) order picking system can be modeled as an M/G/1 queueing problem in which storage and retrieval requests are the customers and the vehicle (NALT or AS/R machine) is the server. Service time is the sum of travel time and the deterministic time to pick up and deposit a pallet (TPD).

Our first contribution is the development of travel time ...

Toolpath Planning Methodology For Multi-Gantry Fused Filament Fabrication 3d Printing, Hieu Trung Bui

Theses and Dissertations

Additive manufacturing (AM) has revolutionized the way industries manufacture and prototype products. Fused filament fabrication (FFF) is one of the most popular processes in AM as it is inexpensive, requires low maintenance, and has high material utilization. However, the biggest drawback that prevents FFF printing from being widely implemented in large-scale production is the cycle time. The most practical approach is to allow multiple collaborating printheads to work simultaneously on different parts of the same object. However, little research has been introduced to support the aforementioned approach. Hence a new toolpath planning methodology is proposed in this paper. The objectives ...

Identifying And Mitigating Supply Chain Risks Using Fault Tree Optimization, Michael D. Sherwin, Hugh R. Medal, Cameron A. Mackenzie, Kennedy J. Brown

Industrial and Manufacturing Systems Engineering Publications

Although supply chain risk management and supply chain reliability are topics that have been studied extensively, a gap exists for solutions that take a systems approach to quantitative risk mitigation decision making and especially in industries that present unique risks. In practice, supply chain risk mitigation decisions are made in silos and are reactionary. In this article, we address these gaps by representing a supply chain as a system using a fault tree based on the bill of materials of the product being sourced. Viewing the supply chain as a system provides the basis to develop an approach that considers ...

Optimizing Ensemble Weights For Machine Learning Models: A Case Study For Housing Price Prediction, Mohsen Shahhosseini, Guiping Hu, Hieu Pham

Mohsen Shahhosseini

Designing ensemble learners has been recognized as one of the significant trends in the field of data knowledge especially in data science competitions. Building models that are able to outperform all individual models in terms of bias, which is the error due to the difference in the average model predictions and actual values, and variance, which is the variability of model predictions, has been the main goal of the studies in this area. An optimization model has been proposed in this paper to design ensembles that try to minimize bias and variance of predictions. Focusing on service sciences, two well-known ...

Minimodal: Dimensional Domain Of Miniature Shipping Containers For Intermodal Freight Transportation, Lee Stapley

Ursidae: The Undergraduate Research Journal at the University of Northern Colorado

This study explores the feasibility of miniature shipping container usage within existing intermodal transportation (IT) supply chains. Smaller intermodal container shipments may help realign freight shipments with the most efficient transportation mode, rail. These containers embolden the dimensional domain (DD) of shipping. The shipping container dimensional domain (container size variation and modal fluidity) is widespread and results in shipments that are often larger or more infrequent than needed. The DD impacts transport mode, shipping frequency, shipment velocity, intermodal supply chain accessibility, and regional shipping networks. This study suggests that container size impacts the DD and, therefore, mode choice. As miniature ...

Data Clustering Using Proximity Matrices With Missing Values, Samira Karimzadeh, Sigurdur Olafsson

Industrial and Manufacturing Systems Engineering Publications

In most applications of data clustering the input data includes vectors describing the location of each data point, from which distances between data points can be calculated and a proximity matrix constructed. In some applications, however, the only available input is the proximity matrix, that is, the distances between each pair of data point. Several clustering algorithms can still be applied, but if the proximity matrix has missing values no standard method is directly applicable. Imputation can be done to replace missing values, but most imputation methods do not apply when only the proximity matrix is available. As a partial ...