Simulation Based Optimization in Fishery Management

The sea scallop resource of Georges Bank supports one of the largest commercial fisheries in the United States. The objective of this research was to develop a technique to examine different management strategies for the sea scallop resource of Georges Bank and compare these strategies to the optimal. A simulation model followed the sea scallop population dynamics using information from recent photographic surveys and studies on spatial and temporal life history parameters, such as growth, natural mortality, spawning, and fishing activities. Stochastic simulation technique was used to describe the influence of the highly variable marine environment. Genetic Algorithm technique was used to develop harvest strategy in the area for optimal utilization by maximizing long term fishing yield. Simulation and Genetic Algorithm are combined to solve the optimization problem. Simulation returns performance measures for a given policy and Genetic Algorithm provides the search process to obtain the optimum policy.