Optimal sustainable harvesting of populations in random environments

STOCHASTIC PROCESSES AND THEIR APPLICATIONS

卷:150

Article

Alvarez, Luis H. R.¹  Hening, Alexandru² 

[1] Univ Turku, Turku Sch Econ, Dept Accounting & Finance, FIN-20014 Turku, Finland

[2] Tufts Univ, Dept Math, 503 Boston Ave, Medford, MA 02155 USA

关键词: Ergodic control;    Stochastic harvesting;    Ergodicity;    Stochastic logistic model;    Stochastic environment;   

DOI  :  10.1016/j.spa.2019.02.008

来源: Elsevier

【 摘 要 】

We study the optimal sustainable harvesting of a population that lives in a random environment. The novelty of our setting is that we maximize the asymptotic harvesting yield, both in an expected value and almost sure sense, for a large class of harvesting strategies and unstructured population models. We prove under relatively weak assumptions that there exists a unique optimal harvesting strategy characterized by an optimal threshold below which the population is maintained at all times by utilizing a local time push-type policy. We also discuss, through Abelian limits, how our results are related to the optimal harvesting strategies when one maximizes the expected cumulative present value of the harvesting yield and establish a simple connection and ordering between the values and optimal boundaries. Finally, we explicitly characterize the optimal harvesting strategies in two different cases, one of which is the celebrated stochastic Verhulst Pearl logistic model of population growth. ?c 2019 Elsevier B.V. All rights reserved.

【 授权许可】

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