CAREER: Dynamic Invasive Species Control Optimization Via Integrated Education and Research (DISCOVER)

职业：通过综合教育和研究进行动态入侵物种控制优化（发现）

• 批准号: 1554018
• 负责人: Esra Buyuktahtakin Toy
• 金额: $ 50万
• 依托单位: Wichita State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-03-01 至 2018-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1554018&HistoricalAwards=false
• 关键词: CAREER; Dynamic; Invasive; Species; Control

1554018 (Buyuktahtakin). The goal of this research is to design optimal intervention and resource allocation strategies to protect ecological systems from the detrimental impacts of invasive species. This research goal will be pursued through four specific objectives: (1) designing a novel mathematical optimization framework; (2) investigating a new class of game theoretic problems to coordinate multiple stakeholders (e.g., government, land managers, cooperatives) in invasive species management and provide insight into public policy decisions; (3) formulating and solving novel surveillance and control problems under uncertainty; and (4) performing experiments to demonstrate the potential benefit of the proposed models and algorithms by using real-life cases. The education objective of this CAREER program is to create decision models for use in outreach, educational, and management activities; in return, interactions with stakeholders, students, and teachers will provide feedback for designing cutting-edge and practical mathematical models.The research efforts will include: (1) design of a novel decomposition-based optimization framework that will help to overcome a big challenge of computational complexity in spatio-temporal optimization; (2) development of rigorous optimization models and methods to solve high-dimensional resource allocation problems in environmental management; (3) development of a decision support tool to provide efficient management practices for invasive species management, in collaboration with ecologists, managers, and policy makers; (4) advancements in theory and methodology through a rigorous analysis of uncertainty and novel surveillance and control modeling; (5) a new class of game theoretic models and algorithms that can be used to provide fundamental insights into the design of public policies for environmental management; and (6) modeling, algorithmic, and computational advances in discrete optimization, which potentially may help solve other important optimization problems.This award is co-funded by the CBET/ENG Environmental Sustainability program and the DMS/MPS Division under BioMaPs.

1554018 (Buyuktahtakin)。本研究的目的是设计最佳的干预和资源配置策略，以保护生态系统免受入侵物种的有害影响。本研究目标将通过四个具体目标来实现：(1)设计一个新的数学优化框架；(2)研究一类新的博弈论问题，以协调入侵物种管理中的多个利益相关者（如政府、土地管理者、合作社），并为公共政策决策提供见解；(3)制定和解决不确定性下的新型监控问题；(4)通过实际案例进行实验，以证明所提出的模型和算法的潜在效益。该职业计划的教育目标是创建用于外展，教育和管理活动的决策模型；作为回报，与利益相关者、学生和老师的互动将为设计前沿和实用的数学模型提供反馈。研究工作将包括：(1)设计一种新的基于分解的优化框架，这将有助于克服时空优化中计算复杂性的巨大挑战；(2)建立严格的优化模型和方法，解决环境管理中的高维资源配置问题；(3)与生态学家、管理者和政策制定者合作，开发决策支持工具，为入侵物种管理提供有效的管理实践；(4)通过对不确定性的严格分析和新颖的监测和控制模型，在理论和方法上取得了进步；(5)一类新的博弈论模型和算法，可用于为环境管理公共政策的设计提供基本见解；(6)离散优化中的建模、算法和计算进步，这可能有助于解决其他重要的优化问题。该奖项由CBET/ENG环境可持续性项目和生物生物计划下的DMS/MPS部门共同资助。