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Environmental Modeling & Assessment

, Volume 23, Issue 6, pp 743–752 | Cite as

A Robust Optimization Model for an Invasive Species Management Problem

  • Nahid JafariEmail author
  • Austin Phillips
  • Panos M. Pardalos
Article
  • 137 Downloads

Abstract

Invasive species pose a significant threat to global biodiversity. Managing invasive species often involves modeling the species’ spread pattern, estimating control costs and damage costs due to the invasion, designing control efforts, and accounting for uncertainties in model parameters. Dealing with uncertainty is arguably the most important part of the process, since biological, environmental, and economic factors can cause parameter values to vary greatly. Managers need decision tools that are robust to such limited or variable information. Here, we present a robust spatial optimization model to select treatment sites in a way that maximally reduces the size of an invasive population, given a constraint on financial resources. We develop an integer programming model that includes population dynamics and management costs over space and time. The model incorporates uncertainty in the available budget and the invasive spread rate as sets of discrete scenarios to determine a robust, cost-effective management plan in a novel way.

Keywords

Invasive species management Site selection problem Integer programming Parameter uncertainty Robust optimization 

Notes

Acknowledgements

Panos M. Pardalos was partially supported by the Paul and Heidi Brown Preeminent Professorship in ISE at the University of Florida.

The authors thank anonymous reviewers for helpful comments that have enhanced this paper.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Nahid Jafari
    • 1
  • Austin Phillips
    • 2
  • Panos M. Pardalos
    • 3
  1. 1.School of BusinessFarmingdale State College (SUNY)FarmingdaleUSA
  2. 2.Woods Hole Oceanographic InstituteWoods HoleUSA
  3. 3.Center for Applied OptimizationUniversity of FloridaGainesvilleUSA

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