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A multi-objective optimization approach for invasive species control

Author

Listed:
  • I Esra Buyuktahtakin

    (Wichita State University, Wichita, USA)

  • Zhuo Feng

    (Arizona State University, Phoenix, USA)

  • Ferenc Szidarovszky

    (1] Arizona State University, Phoenix, USA[2] University of Pécs, Pécs, Hungary)

Abstract
In this paper, we formulate and analyse a long-term multi-objective dynamic model for controlling invasive species. This optimization framework is then applied to the case of buffelgrass control in the Arizona desert. The proposed model simultaneously optimizes three objectives corresponding to three different valued and threatened resources including saguaros (a native cactus species), buildings and vegetation. The model is used to decide the optimal allocation of labour to these resources to control the population of the species in a multi-period planning horizon. The computational method to solve this problem is based on multi-objective integer programming.

Suggested Citation

  • I Esra Buyuktahtakin & Zhuo Feng & Ferenc Szidarovszky, 2014. "A multi-objective optimization approach for invasive species control," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(11), pages 1625-1635, November.
    • Handle: RePEc:pal:jorsoc:v:65:y:2014:i:11:p:1625-1635
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    Citations

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    Cited by:

    1. Kıbış, Eyyüb Y. & Büyüktahtakın, İ. Esra, 2017. "Optimizing invasive species management: A mixed-integer linear programming approach," European Journal of Operational Research, Elsevier, vol. 259(1), pages 308-321.
    2. İ. Esra Büyüktahtakın & Robert G. Haight, 2018. "A review of operations research models in invasive species management: state of the art, challenges, and future directions," Annals of Operations Research, Springer, vol. 271(2), pages 357-403, December.
    3. Onal, Sevilay & Akhundov, Najmaddin & Büyüktahtakın, İ. Esra & Smith, Jennifer & Houseman, Gregory R., 2020. "An integrated simulation-optimization framework to optimize search and treatment path for controlling a biological invader," International Journal of Production Economics, Elsevier, vol. 222(C).
    4. Eyyüb Y. Kıbış & İ. Esra Büyüktahtakın & Robert G. Haight & Najmaddin Akhundov & Kathleen Knight & Charles E. Flower, 2021. "A Multistage Stochastic Programming Approach to the Optimal Surveillance and Control of the Emerald Ash Borer in Cities," INFORMS Journal on Computing, INFORMS, vol. 33(2), pages 808-834, May.
    5. Haider, Zulqarnain & Charkhgard, Hadi & Kwon, Changhyun, 2018. "A robust optimization approach for solving problems in conservation planning," Ecological Modelling, Elsevier, vol. 368(C), pages 288-297.

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