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Combinatorial optimization and decision-making with applications in Computational Sustainability

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dc.contributor.authorShi, Qinru
dc.contributor.chairGomes, Carla P.
dc.contributor.committeeMemberBindel, David S.
dc.contributor.committeeMemberDavis, Damek Shea
dc.date.accessioned2022-10-31T16:20:45Z
dc.date.available2022-10-31T16:20:45Z
dc.date.issued2022-08
dc.description133 pages
dc.description.abstractCombinatorial optimization and decision-making problems are critical in many real-world computational sustainability problems. The main goals for these projects are often to provide decision-support tools for various groups and institutions to help solve complex computation problems encountered in sustainable planning and development. This thesis mainly focuses on two real-world applications of combinatorial optimization and decision-making in computational sustainability. The first is a multiobjective optimization problem inspired by the real-world problem of placing hydropower dams in the Amazon basin. We propose a fully polynomial-time approximation scheme based on Dynamic Programming (DP) for computing the Pareto frontier within an arbitrarily small error margin on tree-structured networks. We also developed a complementary mixed integer programming (MIP) approach for approximating the Pareto frontier and methods for approximating high-dimensional Pareto frontiers. The second is an online matching problem coordinating citizen scientists for invasive species survey efforts. We developed a learning-augmented matching algorithm that can utilize partial information and provides good performance and approximation guarantees. For both applications, we provide not only practical solutions to real-world problems but also novel computational algorithms and techniques.
dc.identifier.doihttps://doi.org/10.7298/kyf4-n534
dc.identifier.otherShi_cornellgrad_0058F_13277
dc.identifier.otherhttp://dissertations.umi.com/cornellgrad:13277
dc.identifier.urihttps://hdl.handle.net/1813/112054
dc.language.isoen
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectApproximation Algorithm
dc.subjectCombinatorial Optimization
dc.subjectComputational Sustainability
dc.subjectHydropower
dc.subjectMultiobjective Optimization
dc.titleCombinatorial optimization and decision-making with applications in Computational Sustainability
dc.typedissertation or thesis
dcterms.licensehttps://hdl.handle.net/1813/59810.2
thesis.degree.disciplineApplied Mathematics
thesis.degree.grantorCornell University
thesis.degree.levelDoctor of Philosophy
thesis.degree.namePh. D., Applied Mathematics

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