Use of Multiattribute Utility Theory for Designing Invertebrate Fisheries Sampling Programs

Abstract Multiattribute utility theory (MAUT) and integer programming are employed to examine optimal sampling strategies for commercial invertebrate fisheries in British Columbia, Canada. Attributes considered in the study take into account various biological, economic, social, and political aspects of the fisheries. Twenty-six fishery managers, biologists, and researchers from the Department of Fisheries and Oceans participated in ranking and assigning weights to each of the attributes to provide overall utility scores. Integer programming was then employed to generate optimal sampling strategies subject to various cost, personnel, area, and fishery constraints. The results clearly demonstrate the potential usefulness of MAUT analysis for developing strategies to monitor commercial invertebrate fisheries.