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Algorithmic Sustainability for Resource Allocation in Large-Scale Sociotechnical Systems
Algorithmic Sustainability for Resource Allocation in Large-Scale Sociotechnical Systems
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202104736
- ISBN
- 9798290649603
- DDC
- 519
- 저자명
- Jalota, Devansh.
- 서명/저자
- Algorithmic Sustainability for Resource Allocation in Large-Scale Sociotechnical Systems
- 발행사항
- [Sl] : Stanford University, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 663 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-03, Section: A.
- 주기사항
- Advisor: Pavone, Marco;Ye, Yinyu.
- 학위논문주기
- Thesis (Ph.D.)--Stanford University, 2025.
- 초록/해제
- 요약Technological advances have opened new avenues for designing market mechanisms for resource allocation in sociotechnical and urban infrastructure systems, from enhancing resource allocation efficiency with widespread data availability to enabling real-time algorithm implementation. While these technological advancements hold significant promise, they also introduce new societal challenges related to equity, privacy, data uncertainty, and security that existing market mechanisms often fail to address. In response, this thesis develops data-driven and online learning algorithms and incentive schemes that confront these shortcomings of traditional market mechanisms, thereby advancing the science and practice of market design for socially sustainable resource allocation in large-scale sociotechnical and urban infrastructure systems. Spanning both foundational and application-driven research, with an emphasis on transportation and smart mobility applications, this thesis is divided into four parts, each addressing a different aspect of social sustainability.Part I focuses on addressing the privacy and information availability concerns of traditional equilibrium pricing problems, which require observing user attributes to make pricing and allocation decisions. Specifically, we generalize classical equilibrium pricing problems in transportation, electricity, and Fisher markets to online incomplete information settings and design novel posted-price mechanisms relying solely on revealed preference feedback (i.e., past observations of user consumption) with provably strong performance guarantees.In Parts II and III, we turn to another dimension of social sustainability, that of fairness and equity, which are key considerations across a range of equilibrium pricing and game-theoretic applications in large-scale sociotechnical systems. Part II extends classical market equilibrium models in two-sided matching and Fisher markets to accommodate additional constraints arising from fairness considerations, developing algorithms for large-scale equilibrium computation in these enriched settings. Part III continues the exploration of fairness and equity by addressing the inequity concerns that have hindered the practical deployment of congestion pricing, an AI-powered trac mitigation strategy. Spurred by collaborations with government agencies, we propose novel congestion pricing schemes to balance the efficiency and equity goals of sustainable transportation and develop robust theoretical frameworks to assess the impact of these schemes on trac and equity outcomes. In doing so, our work develops methods to pave the way for designing sustainable and publicly acceptable congestion pricing schemes, shifting the discussion from the regressive impacts of congestion pricing to one that centers around how to best preserve equity.Finally, Part IV focuses on a third social sustainability dimension: security. We design enforcement mechanisms to mitigate user fraud, with an emphasis on smart mobility applications, and leverage problem structure to make fundamental algorithmic contributions to societal-scale equilibrium computation problems in security games.
- 일반주제명
- Linear programming
- 일반주제명
- Public safety
- 일반주제명
- Distance learning
- 일반주제명
- Urban planning
- 일반주제명
- Sustainability
- 키워드
- Data uncertainty
- 기타저자
- Stanford University.
- 기본자료저록
- Dissertations Abstracts International. 87-03A.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520260202104736
■006m o d
■007cr#unu||||||||
■020 ▼a9798290649603
■035 ▼a(MiAaPQ)AAI32149655
■035 ▼a(MiAaPQ)Stanfordgj925tz2253
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a519
■1001 ▼aJalota, Devansh.
■24510▼aAlgorithmic Sustainability for Resource Allocation in Large-Scale Sociotechnical Systems
■260 ▼a[Sl]▼bStanford University▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a663 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-03, Section: A.
■500 ▼aAdvisor: Pavone, Marco;Ye, Yinyu.
■5021 ▼aThesis (Ph.D.)--Stanford University, 2025.
■520 ▼aTechnological advances have opened new avenues for designing market mechanisms for resource allocation in sociotechnical and urban infrastructure systems, from enhancing resource allocation efficiency with widespread data availability to enabling real-time algorithm implementation. While these technological advancements hold significant promise, they also introduce new societal challenges related to equity, privacy, data uncertainty, and security that existing market mechanisms often fail to address. In response, this thesis develops data-driven and online learning algorithms and incentive schemes that confront these shortcomings of traditional market mechanisms, thereby advancing the science and practice of market design for socially sustainable resource allocation in large-scale sociotechnical and urban infrastructure systems. Spanning both foundational and application-driven research, with an emphasis on transportation and smart mobility applications, this thesis is divided into four parts, each addressing a different aspect of social sustainability.Part I focuses on addressing the privacy and information availability concerns of traditional equilibrium pricing problems, which require observing user attributes to make pricing and allocation decisions. Specifically, we generalize classical equilibrium pricing problems in transportation, electricity, and Fisher markets to online incomplete information settings and design novel posted-price mechanisms relying solely on revealed preference feedback (i.e., past observations of user consumption) with provably strong performance guarantees.In Parts II and III, we turn to another dimension of social sustainability, that of fairness and equity, which are key considerations across a range of equilibrium pricing and game-theoretic applications in large-scale sociotechnical systems. Part II extends classical market equilibrium models in two-sided matching and Fisher markets to accommodate additional constraints arising from fairness considerations, developing algorithms for large-scale equilibrium computation in these enriched settings. Part III continues the exploration of fairness and equity by addressing the inequity concerns that have hindered the practical deployment of congestion pricing, an AI-powered trac mitigation strategy. Spurred by collaborations with government agencies, we propose novel congestion pricing schemes to balance the efficiency and equity goals of sustainable transportation and develop robust theoretical frameworks to assess the impact of these schemes on trac and equity outcomes. In doing so, our work develops methods to pave the way for designing sustainable and publicly acceptable congestion pricing schemes, shifting the discussion from the regressive impacts of congestion pricing to one that centers around how to best preserve equity.Finally, Part IV focuses on a third social sustainability dimension: security. We design enforcement mechanisms to mitigate user fraud, with an emphasis on smart mobility applications, and leverage problem structure to make fundamental algorithmic contributions to societal-scale equilibrium computation problems in security games.
■590 ▼aSchool code: 0212.
■650 4▼aLinear programming
■650 4▼aPublic safety
■650 4▼aDistance learning
■650 4▼aUrban planning
■650 4▼aSustainability
■653 ▼aData uncertainty
■653 ▼aMarket mechanisms
■690 ▼a0640
■690 ▼a0999
■71020▼aStanford University.
■7730 ▼tDissertations Abstracts International▼g87-03A.
■790 ▼a0212
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17358682▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
