Operational Research Commons^™

Multi-City Travel Routing Tool: Reducing Travel Costs And Time Spent Planning Using Apis, Trey R. Merreighn

Industrial Engineering Undergraduate Honors Theses

Travel planning is a time-consuming and ever-changing problem that can diminish the travel experience and greatly increase expenditure, if not done correctly. It is important to have an easy travel planning experience so you can enjoy the travel experience more and not waste time where it is not needed. This thesis aims to minimize the costs and time spent on travel planning using APIs and simple optimization models, creating a travel planning tool. This travel planning tool was developed in Java with the main API being Amadeus, this was combined with a greedy best-permutation heuristic to create the main route …

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.

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 …

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 …

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 …

Linear Programming By G.V. Shenoy, New Delhi: Wiley Eastern Limited, 1989., A K Rao

IIMB Management Review

No abstract provided.