OU - Graduate Student Publications
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Browsing OU - Graduate Student Publications by College/Department "Gallogly College of Engineering::School of Industrial and Systems Engineering"
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Item Open Access Benchmarking of Academic Departments using Data Envelopment Analysis (DEA)(2022-04-01) Alam, T.E.; Gonzalez, A.D.; Raman, S.Purpose – The main objective of the paper is to develop an Investment Model using Data Envelopment Analysis (DEA) that provides a decision-making framework to allocate resources efficiently, such that the relative efficiency is improved within an available investment budget. Design/methodology/approach – DEA models are used to evaluate the efficiency of the departments relative to their peers and providing benchmarks for the less efficient departments. Secondly, the inefficiencies in departments are identified. Finally, for the less efficient departments, a decision-support system is introduced for optimizing resource allocation to improve efficiency. Findings – Five of the eighteen academic departments were determined to be inefficient, and benchmark departments were found for those departments. The most prevalent causes for inefficiency were the number of Undergraduate Students per Faculty and the Number of Graduate Students. Results from the Investment Model for Department 12 suggest increasing the Number of Faculty by 2 units and H-Index by 0.5 units, thereby, improving the relative efficiency of the department by 6.8% (88% to 94%), using $290,000 out of $500,000 investment budget provided. Originality – When an investment budget is available, no study has used DEA to develop a decision-support framework for resource allocation in academic departments to maximize relative efficiency.Item Open Access Optimal Selection of Short-and Long-Term Mitigation Strategies for Buildings within Communities under Flooding Hazard(2022-08-09) Gupta, Himadri Sen; Nofal, Omar M.; González, Andrés D.; Nicholson, Charles D.; van de Lindt, John W.Every year, floods cause substantial economic losses worldwide with devastating impacts on buildings and physical infrastructures throughout communities. Techniques are available to mitigate flood damage and subsequent losses, but the ability to weigh such strategies with respect to their benefits from a community resilience perspective is limited in the literature. Investing in flood mitigation is critical for communities to protect the physical and socioeconomic systems that depend on them. While there are multiple mitigation options to implement at the building level, this paper focuses on determining the optimal flood mitigation strategy for buildings to minimize flood losses within a community. In this research, a mixed integer linear programming model is proposed for studying the effects and trade-offs associated with pre-event short-term and long-term mitigation strategies to minimize the expected economic losses associated with floods. The capabilities of the proposed model are illustrated for Lumberton, North Carolina (NC), a small, socially diverse inland community on the Lumber River. The mathematically optimal building-level flood mitigation plan is provided based on the available budget, which can significantly minimize the total expected direct economic loss of the community. The results reveal important correlations among investment quantity, building-level short- and long-term mitigation measures, flood depths of various locations, and buildings’ structure. Additionally, this study shows the trade-offs between short- and long-term mitigation measures based on available budget by providing decision support to building owners regarding mitigation measures for their buildings.