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Commun. Math. Biol. Neurosci. 2019 (2019), Article ID 17

An ecological model for sustainable wildlife management of the Sundarbans' eco-system based on optimal control theory

Md. Nazmul Hasan, Md. Haider Ali Biswas, Md. Sharif Uddin

Abstract

The threats to wildlife in Sundarban, the largest mangrove forest in the world arepoaching, recurrent coastal flooding, cyclone and toxicity. Optimal control theory is applied toinvestigate optimal strategies for controlling these threats in the system where anti-poaching patrolsare used for poaching, strong Bomas are constructed to stopping retaliatory killing, green fenceis built for controlling coastal flood and cyclone and re-rout is applied for for toxic control. Thecombination of the three controls is used to control its possible impact on the threats that thepredator prey facing in Sundarbans. The system is also examined so that the best result is achieved.In this study we have also analyzed the optimal control theory where the existing condition isdiscussed. However different control strategies are considered and the achieved results are discussedtogether with the effect of variation of prey refuge.

Published
21 June 2019
Volume
2019 (2019)
License
CC BY 3.0

Copyright © 2019 Md. Nazmul Hasan, Md. Haider Ali Biswas, Md. Sharif Uddin. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Cite this article

M. N. Hasan, M. H. Ali Biswas, M. S. Uddin, An ecological model for sustainable wildlife management of the Sundarbans' eco-system based on optimal control theory, Commun. Math. Biol. Neurosci. 2019 (2019), 17. https://doi.org/10.28919/cmbn/4058

BibTeX
@article{Hasan2019,
  author  = {Hasan, Md. Nazmul and Ali Biswas, Md. Haider and Uddin, Md. Sharif},
  title   = {An ecological model for sustainable wildlife management of the Sundarbans' eco-system based on optimal control theory},
  journal = {Commun. Math. Biol. Neurosci.},
  volume  = {2019},
  year    = {2019},
  pages   = {17},
  doi     = {10.28919/cmbn/4058}
}