Operational Research Commons^™

Analyzing Failure Classifications For Patterns And Trends, Casey Eaton, Amanda Banks

Von Braun Symposium Student Posters

No abstract provided.

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

Operations Research and Engineering Management

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

Operations Research and Engineering Management

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 34 …

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

Operations Research and Engineering Management 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 …

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

Graduate 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 …

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

Graduate 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 pdfs for retrieval operations …

Control Of Infectious Diseases In A Metapopulation, Ceyda Best

All Dissertations

With the motivation of the complex infectious disease control problem, we provide two different approaches to model the resource allocation problem to control an epidemic in a metapopulation. All of our models utilize a detailed stochastic simulation model that is validated with the data from the 2014 Ebola epidemic. This simulation model provides a tool for comparing the performance of different policies.

The first model defines a dynamic allocation problem, which is modeled by a Markov Decision Process, and aims to find feasible and effective quarantine policies to control an epidemic with limited resources. We assume that the populations share …

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 …

Intelligent Software Tools For Recruiting, Swatee B. Kulkarni, Xiangdong Che

Journal of International Technology and Information Management

In this paper, we outline how recruiting and talent acquisition gained importance within HRM field, then give a brief introduction to the newest tools used by the professionals for recruiting and lastly, describe the Artificial Intelligence-based tools that have started playing an increasingly important role. We also provide further research suggestions for using artificial intelligence-based tools to make recruiting more efficient and cost-effective.

Table Of Contents Jitim Vol 28 Issue 2, 2019

Journal of International Technology and Information Management

Table of Contents JITIM 2, 2019

A Longitudinal Analysis Of The Impact Of The Indicators In The Networked Readiness Index (Nri), Satya Pratipatti, Ahmed Gomaa

Journal of International Technology and Information Management

World Economic Forum publishes the Networked Readiness Index (NRI) annually, to reflect the Information and Communication Technology (ICT) status of different countries. The NRI is developed by aggregating 53 indicators. The study identifies the most critical indicators to focus on, to improve the NRI status of countries at different stages of economic development. It uses data from 117 countries and analyzes the changes in the indicators along with their impacts between the years 2012 and 2016. The study explores the differences between countries by grouping them into four groups based on their NRI status. The analysis identifies six indicators with …

Application Of Big Data Analytics In Agriculture Supply Chain Management, Sankara Narayanan Mangalam Ananthapadmanabhan

Master's Theses

The increasing trend in frequency of natural disasters in tandem with globalization of business makes the agricultural supply chain significantly vulnerable to disruption. This thesis presents a pragmatic approach for creating a Business Continuity Model that can notify supply chain planners when there is an increase in risk of agriculture supply chain disruption due to natural disasters. The methodology presented in this thesis applied big data analytics and machine learning algorithms along with agriculture product related exponential decay function to create a regionalized composite risk score, that incorporated both direct and indirect risk associated with the Agriculture Fresh Supply Chain. …

Investigating Consumer Satisfaction Towards Mobile Marketing, Dr Surabhi Singh

Journal of International Technology and Information Management

The extensive applications of mobile phones are visible in global companies for the marketing of their products. The popularity of mobile marketing is increasing considerably. This paper has provided insights into the perspectives of consumer attitude towards mobile marketing in India. The companies will develop an understanding of how mobile marketing influence consumer attitudes. The scale of measurement used for Attitudes was Likert scale and explained the consumer's behavior towards mobile marketing. The factors identified through the study will provide insights into Consumer buying behavior via mobile platforms. The analytical tool SPSS has been used for analysis by using methods …

Persuasion, Political Warfare, And Deterrence: Behavioral And Behaviorally Robust Models, William N. Caballero

Theses and Dissertations

This dissertation examines game theory models in the context of persuasion and competition wherein decision-makers are not completely rational by considering two complementary threads of research. The first thread of research pertains to offensive and preemptively defensive behavioral models. Research in this thread makes three notable contributions. First, an offensive modeling framework is created to identify how an entity optimally influences a populace to take a desired course of action. Second, a defensive modeling framework is defined wherein a regulating entity takes action to bound the behavior of multiple adversaries simultaneously attempting to persuade a group of decision-makers. Third, an …

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.

Fault Adaptive Workload Allocation For Complex Manufacturing Systems, Charlie B. Destefano

Graduate Theses and Dissertations

This research proposes novel fault adaptive workload allocation (FAWA) strategies for the health management of complex manufacturing systems. The primary goal of these strategies is to minimize maintenance costs and maximize production by strategically controlling when and where failures occur through condition-based workload allocation.

For complex systems that are capable of performing tasks a variety of different ways, such as an industrial robot arm that can move between locations using different joint angle configurations and path trajectories, each option, i.e. mission plan, will result in different degradation rates and life-expectancies. Consequently, this can make it difficult to predict when a …

Simulating Alternative Tuberculosis Diagnosis Methods In Underdeveloped Countries, Luke Turner

Industrial Engineering Undergraduate Honors Theses

Tuberculosis is the deadliest infectious disease in the world; it is especially rampant in underdeveloped countries because they do not have the infrastructure, technology, or funding to properly combat the infection. However, the development of portable point-of-care diagnosis machines can reverse this epidemic as they far surpass conventional laboratory identification. The question now is where to place these machines, which is a difficult decision with a lack of data. Therefore, a flexible simulation model is created to test the implementation of these machines with different countries and configurations. The simulation tests the baseline model and three proposed implementations of the …

Crude Oil Price Prediction With Decision Tree Based Regression Approach, Engu Chen, Xin James He

Journal of International Technology and Information Management

Crude oil is an essential commodity for industry and the prediction of its price is crucial for many business entities and government organizations. While there have been quite a few conventional statistical models to forecast oil prices, we find that there is not much research using decision tree models to predict crude oil prices. In this research, we develop decision tree models to forecast crude oil prices. In addition to historical crude oil price time series data, we also use some predictor variables that would potentially affect crude oil prices, including crude oil demand and supply, and monthly GDP and …

A Two-Stage Approach To Ridesharing Assignment And Auction In A Crowdsourcing Collaborative Transportation Platform., Peiyu Luo

Electronic Theses and Dissertations

Collaborative transportation platforms have emerged as an innovative way for firms and individuals to meet their transportation needs through using services from external profit-seeking drivers. A number of collaborative transportation platforms (such as Uber, Lyft, and MyDHL) arise to facilitate such delivery requests in recent years. A particular collaborative transportation platform usually provides a two sided marketplace with one set of members (service seekers or passengers) posting tasks, and the another set of members (service providers or drivers) accepting on these tasks and providing services. As the collaborative transportation platform attracts more service seekers and providers, the number of open …