A decision support system for fish farming using particle swarm optimization

This work presents a Decision Support System (DSS) for fish farming in cages that determines the production strategies that maximize the present profits of the farming process. It is a model-driven cooperative DSS in which the cultivation process is simulated through a bioeconomic model that considers economic, environmental, biological and technical data. The optimal production strategies are determined using Particle Swarm Optimization (PSO). The DSS helps to deal with two types of decisions: operational decisions in which the DSS obtains the optimal solution under particular conditions; and strategic decisions, in which the DSS allows to obtain the optimal economic result in different scenarios. There are a broad range of strategic decisions in which this DSS can be applied, among others, site selection, feed, production capacity, or harvest weight.