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 J
dc.creatorAjayi, Temitayo
dc.date.accessioned2020-08-11T21:44:22Z
dc.date.available2022-08-01T05:01:10Z
dc.date.created2020-08
dc.date.issued2020-08-03
dc.date.submittedAugust 2020
dc.date.updated2020-08-11T21:44:22Z
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.
dc.embargo.terms2022-08-01
dc.format.mimetypeapplication/pdf
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>.
dc.identifier.urihttps://hdl.handle.net/1911/109175
dc.language.isoeng
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.
dc.subjectObjective selection
dc.subjectinverse optimization
dc.subjectradiation therapy
dc.subjectapproximate submodularity
dc.subjectmixed-integer programming
dc.subjectchemotherapy
dc.titleInteger Programming Approaches to Cancer Treatment: Objective Selection in Intensity-Modulated Radiation Therapy and Chemotherapy Treatment Design
dc.typeThesis
dc.type.materialText
thesis.degree.departmentComputational and Applied Mathematics
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy
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