Optimal Harvesting from Interacting Populations in a Stochastic Environment

Abstract

Consider n populations whose sizes are given by stochastic differential equations driven by m-dimensional Brownian motion. We study the following problem: what harvesting strategy from the n populations maximizes the expected total income from the harvest? We formulate this as a (singular) stochastic control problem and give sufficient conditions for the existence of an optimal strategy. Our results lead to the one-at-a-time principle that it is almost surely never optimal to harvest from more than one population at a time.