| NSF Org: |
CMMI Division of Civil, Mechanical, and Manufacturing Innovation |
| Recipient: |
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| Initial Amendment Date: | July 13, 2018 |
| Latest Amendment Date: | June 12, 2024 |
| Award Number: | 1763108 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Reha Uzsoy
ruzsoy@nsf.gov (703)292-2681 CMMI Division of Civil, Mechanical, and Manufacturing Innovation ENG Directorate for Engineering |
| Start Date: | July 15, 2018 |
| End Date: | June 30, 2025 (Estimated) |
| Total Intended Award Amount: | $535,335.00 |
| Total Awarded Amount to Date: | $543,335.00 |
| Funds Obligated to Date: |
FY 2020 = $8,000.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
3720 S FLOWER ST FL 3 LOS ANGELES CA US 90033 (213)740-7762 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
3720 S. Flower St. Los Angeles CA US 90089-0001 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | OE Operations Engineering |
| Primary Program Source: |
01002021DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041 |
ABSTRACT
This award will support national health and prosperity by developing large-scale quantitative models for the strategic design of conservation plans to preserve biodiversity. Biodiversity is essential to human survival on Earth. A key strategy for preserving biodiversity involves making strategic land use decisions over time to create a system of habitat reserves. Long-term planning for these reserves faces challenges due to scarcity of data on species prevalence and resilience, uncertainty about land development activities, and changes over time in the ability of land tracts to sustain diverse species. This project uses a data-driven, computationally efficient robust optimization approach that can assist land use planners in making decisions that affect wildlife and fishery management and that may impact the prosperity of surrounding communities. The project will leverage ongoing collaborations with the United States Geological Survey, as well as Panthera and the Wildlife Conservation Society. The PIs will involve female graduate and undergraduate students in the project through the Women in Science and Engineering program at the University of Southern California. In addition, they will integrate the outcomes of this research into graduate and undergraduate courses they teach.
The project take a rigorous, quantitative approach to conservation planning that utilizes land acquisition and development data to inform novel multi-stage robust optimization models. The framework provides a general modeling scheme for optimization problems under endogenous uncertainty. These models involve binary adaptive decision variables with an exponential number of contingencies whose chance of occurrence is also decision-dependent. Spatio-temporal uncertainty sets are constructed using land use projections obtained from governmental agencies and NGOs. The PIs will extend the K-adaptability approach to the multi-stage setting, and will investigate techniques to provide lower bounds on the optimality gap.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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