Career: Dynamic Invasive Species Control Optimization Via Integrated Education And Research (Discover)

  • Buyuktahtakin-Toy, Ismet (PI)

Project: Research project

Project Details


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.
Effective start/end date9/6/172/28/21


  • National Science Foundation


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