Production Scheduling in the Aquaculture Industry Based on Bio-economic Simulation and Genetic Algorithms

Production scheduling is a key process to optimize the operational activities in most production industries. Aquaculture is not an exception, especially considering that its decision-making processes are especially complex, due to the large number of, external and internal, influencing factors. Furthermore, the industry finds itself going through a difficult time as the competition among companies is at its peak and the new consumers' demands in terms of efficiency and sustainability are increasingly complex. In this context, the application of decision support methods in order to maximize the economic efficiency of operational processes is required more than ever for the advancement of the industry. The objective of this work is to address the production scheduling problem in the case of a fish farm with different production units (cages or tanks). To do this, it integrates a bio-economic model with a genetic algorithm. Results show its utility to generate and evaluate different alternatives, determining the best production schedule in different scenarios.