Economic optimisation in seabream (Sparus aurata) aquaculture production using a particle swarm optimisation algorithm
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ABSTRACT: The purpose of this study is the economic optimisation of seabream farming through the determination of the production strategies that maximise the present operating profits of the cultivation process. The methodology applied is a particle swarm optimisation algorithm based on a bioeconomic model that simulates the process of seabream fattening. The biological submodel consists of three interrelated processes, stocking, growth, and mortality, and the economic submodel considers costs and revenues related to the production process. Application of the algorithm to seabream farming in Spain reveals that the activity is profitable and shows competitive differences associated with location. Additionally, the applications of the particle swarm optimisation algorithm could be of interest for the management of other important species, such as salmon (Salmo salar), catfish (Ictalurus punctatus), or tilapia (Oreochromis niloticus).
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