MULTICRITERIA PRODUCTION OPTIMIZATION IN AQUACULTURE USING POPULATION-BASED METAHEURISTICS

The company's economic performance is, very often, taken into account as the most important criterion for the determination of the optimal strategies in aquaculture farms. However, decision-making in aquaculture is becoming increasingly complex for producers due to the need to consider different aspects, such as product quality or the environmental sustainability, which are sometimes opposing and difficult to integrate. In addition, there is currently a wide range of possible production/market strategies , with specific values for each of these aspects and a very differentiated performance.

In this new context, market competition has increased and the complexity of managing industrial-scale production processes involving biological systems is still a growing problem in aquaculture. All this has led, in many cases, t o a lack of management capacity and an increasing need for expert systems applied to decision-making processes that  maximize the farm efficiency.

Like  in most real-world problems, that maximization process is very complex and time consuming, so conventional optimization techniques could encounter many difficulties when attempting to address it. However, some population-based stochastic optimization techniques inspired by the social behaviour of groups of animals, such as PSO, allows t o overcome this problem.  Thus, it is possible to formulate an objective function and conduct a process of finding the optimal production strategy based on multiple objectives.

In this context, the present work explains the development of a novel methodology, based on the integration of multiple-criteria techniques and population-based metaheuristics, which allows decision-makers to align its production objectives to their preferences in multiple aspects and thus determine the best strategy. Th is directly addresses one of the key challenges in aquaculture in recent years, the ultimate goal of which is to improve efficiency in order to minimize the use of resources and maximize profits.

The results obtained show the utility of this methodology for integrating numerous objectives and prove that in most cases  these techniques improve the company's results. Therefore, we may conclude that this methodology will improve the management capacity of aquaculture producers and their understanding of the performance of the main variables of the farm. Lastly ,  it is important to highlight the importance of the data quality so any effort aimed at increasing information recording and transparency will improve the results of implementing these methodologies.