Modelling the sardine fishing industry of Morocco with dynamic programming

In this paper we use the dynamic programming approach to model the Moroccan sardine fishery system. We show how the elements of the dynamic programming method such as steps, states and actions are used. The proposed model determines the harvest quantity of sardine in each fishing season in order to maximize the total yield over some definite periods. Some numerical tests of the model, in the deterministic case, are presented and their results show that the approach used is promising. Besides determining the optimal harvest policy, our model can address many important issues such as the impacts of introducing new fishery technologies and finding the best dates and periods of the biological break. This can be done by parametric analysis of the appropriate data of the model. Finally, some data are revealed to be crucial to the model validity and require special attention.