Conference Proceeding Article
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.
Management Information Systems | OS and Networks
Information Systems and Management
AAAI Conference on Artificial Intelligence (AAAI): San Franciso, USA, 2017 February 4
City or Country
San Fransisco, USA
WU, Xiaojian; Akshat KUMAR; and SHELDON, Daniel.
Robust optimization for tree-structured stochastic network design. (2017). AAAI Conference on Artificial Intelligence (AAAI): San Franciso, USA, 2017 February 4. 4545-4551. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3528
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