A discrete optimality system for an optimal harvesting problem

Date

2017-10-01

Author

Bakan, Hacer Oz
Yilmaz, Fikriye
Weber, Gerhard Wilhelm

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In this paper, we obtain the discrete optimality system of an optimal harvesting problem. While maximizing a combination of the total expected utility of the consumption and of the terminal size of a population, as a dynamic constraint, we assume that the density of the population is modeled by a stochastic quasi-linear heat equation. Finite-difference and symplectic partitioned Runge-Kutta (SPRK) schemes are used for space and time discretizations, respectively. It is the first time that a SPRK scheme is employed for the optimal control of stochastic partial differential equations. Monte-Carlo simulation is applied to handle expectation appearing in the cost functional. We present our results together with a numerical example. The paper ends with a conclusion and an outlook to future studies, on further research questions and applications.

Subject Keywords

Management Information Systems, Information Systems

URI

https://hdl.handle.net/11511/50466

Journal

COMPUTATIONAL MANAGEMENT SCIENCE

DOI

https://doi.org/10.1007/s10287-017-0286-5

Collections

Graduate School of Applied Mathematics, Article

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Citation Formats

H. O. Bakan, F. Yilmaz, and G. W. Weber, “A discrete optimality system for an optimal harvesting problem,” COMPUTATIONAL MANAGEMENT SCIENCE, pp. 519–533, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/50466.