{"id":{"repo_id":"texas","oai_identifier":"oai:repositories.lib.utexas.edu:2152/71400"},"canonical_url":"https://search.dev.ndltd.org/etd/texas/oai:repositories.lib.utexas.edu:2152/71400","repository":{"repo_id":"texas","name":"University of Texas","base_url":"https://repositories.lib.utexas.edu/server/oai/request"},"display":{"title":"Algorithm and mechanism design with nonlinear preferences","abstract":"In real life, many combinatorial and economic problems have nonlinear objectives and constraints, where the nonlinearities typically arise from different risk preferences, non-rationality, etc. Solving these problems is often computationally hard but can be beneficial by providing more revenue or welfare. 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In this thesis, I am going to investigate three problems: route planning with a nonlinear objective, dynamic mechanism design with agents of bounded rationality, and economic mechanism design with risk-loving buyers.","abstract_has_math":false,"creators":["Yang, Ger"],"institution":"The University of Texas at Austin","degree_name":"Doctor of Philosophy","degree_level":"Doctoral","degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Nikolova, Evdokia"],"committee_chairs":[],"committee_members":["Dimakis, Georgios-Alex","Shakkottai, Sanjay","Tran, Ngoc","de Veciana, Gustavo"],"year":2018,"date_issued":"2018-08","date_published":"2018-08","updated_at":"2026-07-24T05:01:12Z","subjects":["Algorithm design","Mechanism design","Route-planning","Approximation algorithm","Dominant path","Wireless coverage prediction","Hysteresis","Game theory","Risk-loving","Auction","Linear programming","Duality"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["doi:10.15781/T2T14V885"],"render_values":[{"text":"doi:10.15781/T2T14V885","href":"https://doi.org/10.15781/T2T14V885","code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2152/71400","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Nikolova, Evdokia"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Dimakis, Georgios-Alex","Shakkottai, Sanjay","Tran, Ngoc","de Veciana, Gustavo"]},{"key":"dc:creator","label":"Author","values":["Yang, Ger"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2018-12-05T17:17:31Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2018-12-05T17:17:31Z"]},{"key":"dc:date.issued","label":"Date","values":["2018-08"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The University of Texas at Austin"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Algorithm design","Mechanism design","Route-planning","Approximation algorithm","Dominant path","Wireless coverage prediction","Hysteresis","Game theory","Risk-loving","Auction","Linear programming","Duality"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["doi:10.15781/T2T14V885"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/2152/71400"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In real life, many combinatorial and economic problems have nonlinear objectives and constraints, where the nonlinearities typically arise from different risk preferences, non-rationality, etc. Solving these problems is often computationally hard but can be beneficial by providing more revenue or welfare. 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