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Articles 1 - 5 of 5
Full-Text Articles in Engineering
Algorithms For Multi-Objective Mixed Integer Programming Problems, Alvaro Miguel Sierra Altamiranda
Algorithms For Multi-Objective Mixed Integer Programming Problems, Alvaro Miguel Sierra Altamiranda
USF Tampa 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 …
Prioritizing Strategic Cyberspace Lethality, Andrew J. Schoka
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 units …
Essays On Time Series And Machine Learning Techniques For Risk Management, Michael Kotarinos
Essays On Time Series And Machine Learning Techniques For Risk Management, Michael Kotarinos
USF Tampa Graduate Theses and Dissertations
The Capital Asset Pricing Model combined with the Sharpe ratio is a standard method for choosing assets for selection in a portfolio. However, this method has many structural issues and was designed for a time when high dimensional computing was in its infancy. An alternative to these methods using a mix of Multi-Level Time Series Clustering, the MACBETH algorithm and traditional time series techniques was constructed that minimized data loss and allow for customized portfolio construction for investors with different risk profiles and specialized investment needs. It was shown that these methods are adaptable to cloud computing environments and allow …
Routing And Designing Networks For Two Transportation Problems, Liu Su
Routing And Designing Networks For Two Transportation Problems, Liu Su
USF Tampa Graduate Theses and Dissertations
Routing and designing are essential for transportation networks. With effective routing and designing policies, transportation networks can work safely and efficiently. There are two transportation problems: hazardous materials (hazmat) transportation and warehouse logistics. This dissertation addresses the routing of networks for both problems. For hazmat transportation, the routing can be regulated via network design. Due to catastrophic consequences of potential accidents in hazmat transportation, a risk-averse approach for routing is necessary. In this dissertation, we consider spectral risk measures, for risk-averse hazmat routing. In addition, we introduce a network design problem to select a set of closed road segments for …
Dynamic Pricing Of Electricity And Demand Response In Smart Communities, Vignesh Subramanian
Dynamic Pricing Of Electricity And Demand Response In Smart Communities, Vignesh Subramanian
USF Tampa Graduate Theses and Dissertations
Grid modernization using advanced metering infrastructure (AMI) will continue to enhance timely communication among the system operator (SO), producers, and consumers. This will further empower the vision of dynamic pricing and demand side management (DSM). The phrase dynamic pricing in this dissertation refers to the practice of disclosing binding prices of electricity just ahead of consumption. As regards DSM, the focus is on collective demand response (DR) by aggregators managing consumers’ loads in smart and connected communities (households, businesses, industries and aggregation of electric vehicle batteries). However, practitioners and researchers alike have expressed the fear that dynamic pricing may cause …