# Dynamic Resource Allocation in Conservation Planning

@inproceedings{Golovin2011DynamicRA, title={Dynamic Resource Allocation in Conservation Planning}, author={Daniel Golovin and Andreas Krause and Beth Gardner and Sarah J. Converse and Steve Morey}, booktitle={AAAI}, year={2011} }

Consider the problem of protecting endangered species by selecting patches of land to be used for conservation purposes. Typically, the availability of patches changes over time, and recommendations must be made dynamically. This is a challenging prototypical example of a sequential optimization problem under uncertainty in computational sustainability. Existing techniques do not scale to problems of realistic size. In this paper, we develop an efficient algorithm for adaptively making…

## 31 Citations

Dynamic Resource Allocation for Optimizing Population Diffusion

- Computer ScienceAISTATS
- 2014

A new approach for computing HOP policies based on mixed-integer programming and dual decomposition is developed, which is eective and scalable compared to existing alternatives.

Sequential Decision Making in Computational Sustainability Through Adaptive Submodularity

- Computer Science
- 2014

This work focuses on sequential decision making under uncertainty in conservation planning, where managers recommend patches of land in order to achieve long-term conservation of biodiversity.

Lagrangian Relaxation Techniques for Scalable Spatial Conservation Planning

- Computer ScienceAAAI
- 2012

This work addresses 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 by exploiting the separable structure present in this problem and using Lagrangian relaxation techniques to gain scalability over the flat representation.

Scheduling Conservation Designs for Maximum Flexibility via Network Cascade Optimization

- Computer ScienceJ. Artif. Intell. Res.
- 2015

This paper considers scheduling purchases in a way that achieves a population spread no less than desired but delays purchases as long as possible, and develops a primal-dual algorithm for the problem that computes both a feasible solution and a bound on the quality of an optimal solution.

Scheduling Conservation Designs via Network Cascade Optimization

- Computer ScienceAAAI
- 2012

A primal-dual algorithm is given for the problem of scheduling land purchases to conserve an endangered species in a way that achieves maximum population spread but delays purchases as long as possible, so that conservation planners retain maximum flexibility and use available budgets in the most efficient way.

Stochastic Network Design for River Networks

- Computer Science
- 2013

A novel approximate algorithm based on the sample average approximation (SAA) and mixed integer programming (MIP) is proposed to efficiently address the problem of using a limited budget to remove instream barriers, which prevent fish from accessing their natural habitat.

Incorporating dynamic distributions into spatial prioritization

- Environmental Science
- 2016

The need to consider dynamic movements in the conservation planning process to ensure that mobile species are adequately protected is highlighted, as a static approach to conservation planning may misdirect resources and lead to inadequate conservation for mobile species.

RESEARCH Incorporating dynamic distributions into spatial prioritization

- Environmental Science
- 2016

Aim Species’ distributions are generally treated as static for the purposes of prioritization, but many species such as migrants and nomads have distributions that shift over time. Decisions about…

Robust Decision Making for Stochastic Network Design

- Computer ScienceAAAI
- 2016

This work is motivated by spatial conservation planning where the goal is to take management decisions within a fixed budget to maximize the expected spread of a population of species over a network of land parcels.

Sequential Decision Making in Computational Sustainability via Adaptive Submodularity

- Computer ScienceAI Mag.
- 2014

The recently discovered notion of adaptive submodularity, an intuitive diminishing returns condition that generalizes the classical notion of submodular set functions to sequential decision problems, is reviewed.

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