Abstract
The distribution of scallop density and size varies spatially as scallops are nearly sessile species and large scallops grow slowly and die naturally at a constant rate, even without fishing. Harvesting scallops at the right time and the right place, therefore, greatly increases the utilization of this renewable resource. This paper presents a simulation-based optimization method for deriving the optimal temporal and spatial scallop harvest strategy. The initial population distribution is estimated through high-resolution video surveys. A simulation model estimates the new population after each harvest through a Markov chain type analysis. The optimal harvest policies are then determined by calculating the amount of scallops to be harvested in each region at any given time period. This optimization process is conducted through an interaction of a genetic algorithm (GA) - based stochastic optimization method and the simulation model.