Optimal harvesting strategies for a multi-cycle and multi-pond shrimp operation: A practical network model

In this paper, we introduce a network formulation of the optimal scheduling model for a multi-cycle and multi-pond shrimp operation grounded on the original optimal harvesting theory for a single production unit. The optimal schedule comprises the harvesting and restocking time that maximizes total profit throughout the planning horizon, bounded by the underlying biological and economic conditions. The model takes into account the information such as harvest size distribution, seasonality of price, temperature and weight-dependent growth, and labor force and market demand constraints. We applied the model to an existing shrimp operation in Hawaii with 40 one-acre ponds and generated the optimal schedule for a year that maximizes overall production. The model schedule is found to be able to increase total production by 5% when compared to the schedule generated using an ''educated'' trial-and-error procedure currently practiced by this operation. Further insights for this multi-cycle and multi-pond scheduling problem were also generated through several alternate simulations. It is found that labor force and market demand constraints are the key factors in scheduling multi-cycle and multi-pond shrimp operations.