Publication Type

Conference Proceeding Article

Publication Date

2-2017

Abstract

Stochastic network design is a general framework for optimizing network connectivity. It has several applications in computational sustainability including spatial conservation planning, pre-disaster network preparation, and river network optimization. A common assumption in previous work has been made that network parameters (e.g., probability of species colonization) are precisely known, which is unrealistic in real- world settings. We therefore address the robust river network design problem where the goal is to optimize river connectivity for fish movement by removing barriers. We assume that fish passability probabilities are known only imprecisely, but are within some interval bounds. We then develop a planning approach that computes the policies with either high robust ratio or low regret. Empirically, our approach scales well to large river networks. We also provide insights into the solutions generated by our robust approach, which has significantly higher robust ratio than the baseline solution with mean parameter estimates.

Discipline

Management Information Systems | OS and Networks

Research Areas

Information Systems and Management

Publication

AAAI Conference on Artificial Intelligence (AAAI): San Franciso, USA, 2017 February 4

First Page

4545

Last Page

4551

Publisher

AAAI

City or Country

San Fransisco, USA

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Comments

Best Paper Award, Computational Sustainability Track

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