A systematic approach to determining mean-variance tradeoffs when managing randomly varying populations

Abstract New results by Henig [3] and White and Kim [11] on multiobjective Markov decision processes are combined with an approach to smooth out year-to-year fluctuations in harvest size, to produce a systematic method for determining mean-variance tradeoffs when harvesting a random population. Further procedures for accelerating computations also are discussed, and a salmon model suggested by Mathews [4] is used to illustrate the procedure. The suggested procedure generalizes Beddington and May [1] and May et al. [5], by presenting a systematic method to determine mean-variance tradeoffs, and secondly by allowing for a much larger class of harvesting policies to be considered.