Integer Programming Approaches to Cancer Treatment: Objective Selection in Intensity-Modulated Radiation Therapy and Chemotherapy Treatment Design

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dc.contributor.advisorSchaefer, Andrew Jen_US
dc.creatorAjayi, Temitayoen_US
dc.date.accessioned2020-08-11T21:44:22Zen_US
dc.date.available2022-08-01T05:01:10Zen_US
dc.date.created2020-08en_US
dc.date.issued2020-08-03en_US
dc.date.submittedAugust 2020en_US
dc.date.updated2020-08-11T21:44:22Zen_US
dc.description.abstractIn this thesis, we present multiple problems that arise in cancer treatment decision-making, and we analyze and implement methods used to solve them. The first problem is the selection of objectives that reflect latent clinical preferences during radiation therapy treatment. By connecting an inverse optimization formulation with greedy and regularized solution approaches, we show that sparse sets of objectives can be retrieved effectively. The development of the greedy forward selection approaches for objective selection leads to an in-depth exploration of the greedy algorithm's performance when the optimized set function is approximately submodular. In addition to the greedy algorithm, we study approximate submodularity in other areas in discrete optimization. The second cancer treatment problem is combination chemotherapy optimization, which requires merging differential equations that model dynamics together with discrete decision variables for complex operational constraints. We formulate this problem as a mixed-integer linear program and solve two models, one that focuses on tumor shrinkage and another that minimizes toxicity.en_US
dc.embargo.terms2022-08-01en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationAjayi, Temitayo. "Integer Programming Approaches to Cancer Treatment: Objective Selection in Intensity-Modulated Radiation Therapy and Chemotherapy Treatment Design." (2020) Diss., Rice University. <a href="https://hdl.handle.net/1911/109175">https://hdl.handle.net/1911/109175</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/109175en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectObjective selectionen_US
dc.subjectinverse optimizationen_US
dc.subjectradiation therapyen_US
dc.subjectapproximate submodularityen_US
dc.subjectmixed-integer programmingen_US
dc.subjectchemotherapyen_US
dc.titleInteger Programming Approaches to Cancer Treatment: Objective Selection in Intensity-Modulated Radiation Therapy and Chemotherapy Treatment Designen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentComputational and Applied Mathematicsen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.nameDoctor of Philosophyen_US
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