QUANTITATIVE METHODS FOR DECISION SUPPORT IN THE ICELANDIC FISHING INDUSTRY

Modern fisheries already collect vast amount of data, for example, through ERP systems and electronic log‐books. It is however well known that the data are rarely used for improving operational decision making. By converting this data into useable information, decision making in the fishing industry could be improved. This paper attempts to show that quantitative methods can be of use in many aspects of decision making in the fishing industry. The paper proposes a hierarchically structured decision support process based on two different optimization models for supporting the long‐ and short‐term decision making in fisheries. For long‐term planning the paper proposes a linear optimization model that describes the entire operation of a vertically integrated seafood company. For short‐term decision making the paper proposes a mixed integer linear optimization model to assist in organizing vessel trips and deciding catch location with regard to raw material quality and yield obtained in processing.