About: Optimal harvesting for a stochastic regime-switching logistic diffusion system with jumps

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Optimal harvesting for a stochastic regime-switching logistic diffusion system with jumps
Creator	Wang, Ke Zou, Xiaoling
Source	Elsevier
abstract	Abstract The optimization problem of fishing for a stochastic logistic model is studied in this paper. Besides a standard geometric Brownian motion, another two driving processes are taken into account: a stationary Poisson point process and a continuous-time finite-state Markov chain. The classical harvesting problem for this model is a big difficult puzzle since the corresponding Fokker–Planck equations with three types of noise are very difficult to solve. Our main goal of this paper is to work out the optimization problem with respect to stationary probability density. One of the main contributions is to provide a new equivalent approach to overcome this problem. More precisely, an ergodic method is used to show the almost surely equivalency between the time averaging yield and sustainable yield. Results show that the optimal strategy changes with environment. An interesting thing is that the optimal strategy for each state is equivalent to the global optimality.
has issue date	2014-08-31(xsd:dateTime)
bibo:doi	10.1016/j.nahs.2014.01.001
has license	els-covid
sha1sum (hex)	eb68173ed9ade0c27573673e9a45ef1be8191edc
schema:url	https://doi.org/10.1016/j.nahs.2014.01.001
resource representing a document's title	Optimal harvesting for a stochastic regime-switching logistic diffusion system with jumps
schema:publication	Nonlinear Analysis: Hybrid Systems
resource representing a document's body	covid:eb68173ed9ade0c27573673e9a45ef1be8191edc#body_text
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