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Optimal harvesting of a logistic population in an environment with stochastic jumps. (English) Zbl 0592.92025

Summary: Dynamic programming is employed to examine the effects of large, sudden changes in population size on the optimal harvest strategy of an exploited resource population. These changes are either adverse or favorable and are assumed to occur at times of events of a Poisson process. The amplitude of these jumps is assumed to be density independent. In between the jumps the population is assumed to grow logistically.
The Bellman equation for the optimal discounted present value is solved numerically and the optimal feedback control computed for the random jump model. The results are compared to the corresponding results for the quasi-deterministic approximation.
In addition, the sensitivity of the results to the discount rate, the total jump rate and the quadratic cost factor is investigated. The optimal results are most strongly sensitive to the rate of stochastic jumps and to the quadratic cost factor to a lesser extent when the deterministic bioeconomic parameters are taken from aggregate antarctic pelagic whaling data.

MSC:

92D40 Ecology
93E20 Optimal stochastic control
92D25 Population dynamics (general)
90C39 Dynamic programming
90C90 Applications of mathematical programming
Full Text: DOI

References:

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