Optimal Harvesting of Stochastically Fluctuating Populations Driven by a Generalized Logistic SDE Growth Model

We describe the growth dynamics of a stock using stochastic differential equations with generalized logistic model which encompasses several well-known functions as special cases. For each model, we compute optimal variable effort policy and compare expected net present value total profit earned by harvester among policies. In addition, further extend study to include parameters sensitivity, such costs volatility, an explicitly Crank–Nicolson discretization scheme necessary obtain