Engineering Commons^™

The Precedence-Constrained Quadratic Knapsack Problem, Changkun Guan

Honors Theses

This thesis investigates the previously unstudied Precedence-Constrained Quadratic Knapsack Problem (PC-QKP), an NP-hard nonlinear combinatorial optimization problem. The PC-QKP is a variation of the traditional Knapsack Problem (KP) that introduces several additional complexities. By developing custom exact and approximate solution methods, and testing these on a wide range of carefully structured PC-QKP problem instances, we seek to identify and understand patterns that make some cases easier or harder to solve than others. The findings aim to help develop better strategies for solving this and similar problems in the future.

Optimizing Wedding Venue Selection Process Using Integer Programming, Luis Rodriguez

Theses/Capstones/Creative Projects

Choosing the right wedding venue can be extremely difficult for the unsuspecting engaged couple. There is a myriad of variables that must be taken into account prior to the illustrious wedding date; these variables include the option for a reception, the location, and food requirements, to name a few. Consequently, the typical couple seems to spend multiple months researching and visiting many wedding spaces. However, even though months go into planning, it still is not a guarantee that all variables are accounted for. Furthermore, without a wedding planner, these couples may second-guess their chosen site due to seemingly arduous issues …

Integrated Machine Learning And Optimization Approaches, Dogacan Yilmaz

Dissertations

This dissertation focuses on the integration of machine learning and optimization. Specifically, novel machine learning-based frameworks are proposed to help solve a broad range of well-known operations research problems to reduce the solution times. The first study presents a bidirectional Long Short-Term Memory framework to learn optimal solutions to sequential decision-making problems. Computational results show that the framework significantly reduces the solution time of benchmark capacitated lot-sizing problems without much loss in feasibility and optimality. Also, models trained using shorter planning horizons can successfully predict the optimal solution of the instances with longer planning horizons. For the hardest data set, …

Academic Advising Support Tool: An Optimization Approach, Spencer Loper

Industrial Engineering Undergraduate Honors Theses

More than ever, a college education is necessary to remain competitive in the job market. Therefore, colleges are dedicating numerous resources to ensure student success. Nonetheless, one of the most important factors of student success is proper academic advising. Students at the University of Arkansas and more specifically within the department of Industrial Engineering department are fortunate to have access to fantastic advising. However, given the volume of students, academic advisors do not have the time to talk through the nuance of every student’s long-term academic plan. The department does provide an eight-semester plan; however, students who have deviated from …

Statistical Modeling, Learning And Computing For Stochastic Dynamics Of Complex Systems, Mohammadmahdi Hajiha

Graduate Theses and Dissertations

With the recent advances in sensor technology, it is much easier to collect and store streams of system operational and environmental (SOE) data. These data can be used as input to model the underlying behavior of complex engineered systems and phenomenons if appropriate algorithms with well-defined assumptions are developed. This dissertation is comprised of the research work to show the applicability of SOE data when fed into proposed tailored algorithms. The first purposes of these algorithms are to estimate and analyze the reliability of a system as elaborated in Chapter 2. This chapter provides the derivation of closed-form expressions that …

Analysis And Modeling Of Strategic Interactions In Health Systems To Improve Patient Care Access, Jorge A. Acuña Melo

USF Tampa Graduate Theses and Dissertations

Affordable health care access that provides well-coordinated and high-quality services on time is a goal that governments and health organizations strive for. Regrettably, most countries deal with access problems that affect the population's health, such as long waiting lists for specialized medical services, overcrowding of emergency departments, and high health prices. In the present doctoral dissertation, I model and analyze the strategic interactions that inhabit the health system machinery to uncover possible structural problems that led to the aforementioned issues. The study involves operation research, data science, and game theory techniques to address the health care access predicament.

Each research …

Locating Relay Nodes To Maximize Wireless Sensor Network Lifetime: A Numerical Study, Maria Rene Arandia Jimenez

Industrial Engineering Undergraduate Honors Theses

A wireless sensor network (WSN) is a group of sensors deployed over an area, which monitor changes in the environment, collects them as data and forwards it between sensors through wireless links. Data is routed, either in a single-hop or multi-hop manner, with the goal of getting this collected data to the sink nodes, which have higher computational capabilities and connects the network with a user interface. Studies have determined that multi-hop WSNs that integrate relay nodes, which function is to only receive and forward data, can maximize lifetime network. A linear programming model, created by Chang and Tassiulas in …

Modeling The Economic Machine Using Bayesian Inference And Statistical Networks, And Optimal Portfolio Construction Using Operations Research, Richard Yang

ENGS 88 Honors Thesis (AB Students)

In this paper, we propose a network-based model to attempt to connect modern macroeconomic theory with real world economic observations and trends. We find that by extending macroeconomic theory with credit leveraging/deleveraging thresholds, we are able to explain economic cycles in addition to long-term growth. Furthermore, we specifically explore the growth-inflation view of the macro economy as a basis for optimal portfolio construction and efficient asset trading. Connecting our network-based macroeconomic model and our optimal portfolio construction algorithm, we create a novel macroeconomic asset-trading framework.

An Engineered Approach To Site Selection: Determining Where Facilities Should Be Located, Kerry Melton

Operations Management Presentations

The importance of facility location has dramatically increased over the last several years as the U.S. economy has expanded and different metropolitan areas and markets have experienced population growth, infrastructure changes, labor availability improvements, and better technologies. Global competition has also created the need to further drive down costs and strategize the location of facilities such as distribution centers, freight consolidation centers, retail stores, manufacturing plants, supplier locations for raw materials, farms to grow crops, port facilities, etc. Due to the importance of facility location, this presentation will consider and evaluate several traditional and more modern methods for determining the …

Biofuel Supply Chain Restructuring -- An Economic Viability And Environmental Sustainability Investigation For Enhancing Second Generation Biofuel Adoption, Rajkamal Kesharwani

Doctoral Dissertations

"Biofuel is a promising clean alternative to fossil fuels. Currently, first generation biofuels are commercially produced by using corn grain as biomass feedstock. However, the use of edible matter of crops, may lead to a competition between food and fuel. Therefore, there is a significant push in both industry and academia to commercialize second generation biofuel manufacturing technology, which uses non-edible matter from crops. Most research focuses on individual manufacturing processes for producing second generation biofuel, but the economic and environmental impacts of a large-scale adoption of second generation biofuel manufacturing have been less widely reported.

This work investigates the …

Improving Efficiencies For The Loading And Packaging Departments At San Luis Sourdough, Alexis Bergstrom, Isabella Pereira, Claudia Robinson

Industrial and Manufacturing Engineering

San Luis Sourdough, currently has issues with efficiency and standardization in their packaging department, ergonomics problems in the packaging department, shipment accuracy in their loading department, and lacks an organized layout design. As a result, four objectives were designed within a six month period. The first was to create standard operating procedures for the packaging department. To inform this decision time studies were performed before and after creating these SOPs. It was discovered that there was a clear need for the SOPs due to variation in packaging efficiency among new and experienced associates. The second set of time studies showed …

Convergent Set-Based Design In Integrated Analysis Of Alternatives: Designing Engineered Resilient Systems, Zephan Wright Wade

Graduate Theses and Dissertations

This thesis presents a comprehensive package for understanding and expanding set-based design quantification through the definition and demonstration of Convergent set-based design (SBD). Convergent SBD is a technique developed for the Engineered Resilient Systems program sponsored by the Department of Defense. Convergent SBD contributes a repeatable methodology with the goal of mathematically eliminating inefficient sets. The study of Convergent SBD led to the development of dominance identification criteria equations using comparison of statistical means. The demonstration of Convergent SBD also illustrates the effect of mission resilience in the tradespace and the impact mission resilience has on preference. Finally, Convergent SBD …

Personalized Decision Modeling For Intervention And Prevention Of Cancers, Fan Wang

Graduate Theses and Dissertations

Personalized medicine has been utilized in all stages of cancer care in recent years, including the prevention, diagnosis, treatment and follow-up. Since prevention and early intervention are particularly crucial in reducing cancer mortalities, personalizing the corresponding strategies and decisions so as to provide the most appropriate or optimal medical services for different patients can greatly improve the current cancer control practices. This dissertation research performs an in-depth exploration of personalized decision modeling of cancer intervention and prevention problems. We investigate the patient-specific screening and vaccination strategies for breast cancer and the cancers related to human papillomavirus (HPV), representatively. Three popular …

Modeling Sustainability In Renewable Energy Supply Chain Systems, Fei Xie

All Dissertations

This dissertation aims at modeling sustainability of renewable fuel supply chain systems against emerging challenges. In particular, the dissertation focuses on the biofuel supply chain system design, and manages to develop advanced modeling framework and corresponding solution methods in tackling challenges in sustaining biofuel supply chain systems. These challenges include: (1) to integrate 'environmental thinking' into the long-term biofuel supply chain planning; (2) to adopt multimodal transportation to mitigate seasonality in biofuel supply chain operations; (3) to provide strategies in hedging against uncertainty from conversion technology; and (4) to develop methodologies in long-term sequential planning of the biofuel supply chain …

Strategic Planning Tool Development Using Portfolio Decision Analysis, Luis B. Vargas Rojas

Graduate Theses and Dissertations

A portfolio decision analysis strategic planning tool was developed for the Facilities Management Office at the University of Arkansas. The tool provides information to support budget allocation decisions based on their Strategic Planning Project List, project attributes (e.g, seat utilization, scheduling preferences, and sustainability rank), and budget constraints. The projects are evaluated using multiobjective decision analysis. We introduce dynamic value functions, which vary the range of the value measures based on the planning horizon, to evaluate the projects). We determine facilities portfolios based on the project values and constraints using Linear Programming. In addition, insightful reports are generated, which provide …

A Set Union Based Formulation For Course Scheduling And Timetabling, Jesse Paul Bukenberger

Master's Theses

The Course Timetabling Problem is a widely studied optimization problem where a number of sections are scheduled in concert with the assignment of students to sections in order to maximize the desirability of the resulting schedule for all stakeholders. This problem is commonly solved as a linear program with variables for each student or group of students with identical schedules. In this paper we explore an alternative formulation that aggregates binary student variables into integer variables denoting the number of students enrolled in a course. Our solution method assumes decomposition of the general schedule into time blocks, and applies a …

Modeling And Optimization Of Resource Allocation In Supply Chain Management Problems, Qi Yuan

Doctoral Dissertations

Resource allocation in supply chain management studies how to allocate the limited available resources economically/optimally to satisfy the demands. It is an important research area in operations research. This dissertation focuses on the modeling and optimization of three problems.

The first part of the dissertation investigates an important and unique problem in a supply chain distribution network, namely minimum cost network flow with variable lower bounds (MCNF-VLB). This type of network can be used to optimize the utilization of distribution channels (i.e., resources) in a large supply network, in order to minimize the total cost while satisfying flow conservation, lower …

Process Optimization Of Boatmate Trailers, Llc, Jamie M. Smotherman, Jasmine L. Kelley

Chancellor’s Honors Program Projects

No abstract provided.

Scheduling Surgical Cases In A Constrained Environment, Bharathwaj Vijayakumar

Browse all Theses and Dissertations

This research examines a complex surgical case scheduling problem for a publicly-funded hospital in the Midwest United States. Publicly-funded hospitals are typically under tight budget constraints and these hospitals strive to maximize the utilization of their resources such as beds, staff, equipment, operating rooms, etc. These resources are relatively fixed for a publically funded hospital. A manual scheduling approach followed by this hospital does not guarantee optimal solutions and consequently has led to large variation in the utilization of resources. This real-world problem is described in this research as a multi-day, multi-resource, and patient-priority-based surgical case scheduling problem with the …

Gains In The Life-Cycle Of Adaptable, Self-Organizing Material Handling Systems, Jan R. Nopper, Guido Follert, Michael Ten Hompel

11th IMHRC Proceedings (Milwaukee, Wisconsin. USA – 2010)

Compared to conventional material flow controls, self-organized material handling systems and the Internet of Things in facility logistics promise several advantages during the life-cycle. Most important is the increased adaptability in case of expansions or modifications due to a consistent modular design; this also promotes an increased robustness due to clearly defined interfaces and a decreased complexity of each module. The use of RFID technology increases the availability of real-time data about the system and the transported units. However, the introduction of self-organized material handling systems also causes costs, e.g. for necessary RFID tags and readers. Against this background, it …

An Object-Based Evolutionary Algorithm: The Nesting Solution, Kanchitpol Ratanapan, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The nesting problems have received considerable attention and have been addressed by a variety of algorithms. Recently, evolutionary algorithms have been adopted for solutions. Most of these algorithms, however, require a search in one-dimensional space; thus a transformation of the problem to a single dimension, as in the sequencing problems, is needed. Unfortunately, this restricts the search space. In this study an object-based evolutionary algorithm for the nesting problems is proposed. The methodology is created in a true two-dimensional space, allowing object-based mechanisms and object-based evolutionary operators to perform effectively on the space without restricting search alternatives. Implementation of the …

An Object-Based Evolutionary Algorithm For Solving Rectangular Piece Nesting Problems, Kanchitpol Ratanapan, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Nesting problems have been tackled by researchers using a vast number of algorithms in the past. Most of the algorithms, however, need to perform on a one-dimensional space. Therefore, the problem must be transformed into a one-dimensional space problem similar to the travelling salesman problem. Consequently, loss of solutions due to the dimensional reduction may occur. In this study, an object-based evolutionary algorithm for rectangular piece nesting problems is proposed. This methodology is created on truly two-dimensional space, allowing new mechanisms (i.e., individual representation, initialization, etc.) and new object-based genetic operators (i.e., hill-climbing, mutation, and recombination operators) to perform effectively …

Simulated Annealing Approach For Solving Stock Cutting Problem, Cihan H. Dagli, Alireza Hajakbari

Engineering Management and Systems Engineering Faculty Research & Creative Works

The simulated annealing approach is applied to stock cutting. The conceptual approach proposed uses an energy function that measures the area of the rectangular enclosure of all the patterns to be nested, the level of similarity between pattern pairs, and the amount of overlap among patterns in evaluating various pattern configurations to be generated by the simulated annealing algorithm. Three methods for pattern configuration generation are considered. The first method uses heuristics to generate the initial configuration. The second and third methods use random selection and random placement of patterns

Possible Applications Of Neural Networks In Manufacturing, S. Lammers, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Summary form only given. An examination is made of the potential of neural networks and the impact of parallel processing in the design and operations of manufacturing systems. After an initial discussion on possible areas of application, an approach that integrates artificial intelligence, operations research, and neural networks for the solution of a scheduling problem is examined