Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

7-2012

Abstract

We address the problem of spatial conservation planning in which the goal is to maximize the expected spread of cascades of an endangered species by strategically purchasing land parcels within a given budget. This problem can be solved by standard integer programming methods using the sample average approximation (SAA) scheme. Our main contribution lies in exploiting the separable structure present in this problem and using Lagrangian relaxation techniques to gain scalability over the flat representation. We also generalize the approach to allow the application of the SAA scheme to a range of stochastic optimization problems. Our iterative approach is highly efficient in terms of space requirements and it provides an upper bound over the optimal solution at each iteration. We apply our approach to the Red-cockaded Woodpecker conservation problem. The results show that it can find the optimal solution significantly faster -- sometimes by an order-of-magnitude -- than using the flat representation for a range of budget sizes.

Discipline

Artificial Intelligence and Robotics | Computer Sciences

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the 26th AAAI Conference on Artificial Intelligence 2012, July 22-26, Toronto, Canada

First Page

309

Last Page

315

ISBN

9781577355687

Publisher

AAAI Press

City or Country

Menlo Park, CA

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