Economic results of pig-fattening systems vary greatly and depend mainly on prices of pork and feeds, and pig growth performance (e.g. feed efficiency, slaughter weight, lean percentage). Previous studies revealed that feeding and shipping strategies are critical factors in the economic outputs of pig production. However, they failed to consider both strategies and the variability in pig growth performance simultaneously. Consequently, we developed a new approach to improve the profitability of pig farms by estimating the best compromise among feeding costs, animal performance, and shipping constraints. We used an individual-based bioeconomic model that simulates the growth of each pig according to its biological traits (e.g. feed intake and protein deposition potential) as a function of different feeding and shipping strategies. The optimization problem is solved using an evolutionary algorithm (CMA-ES, covariance matrix adaptation evolution strategy) that manages the objective function, which is discontinuous, non-convex, nonlinear, and multimodal. Various case studies were constructed to investigate the behavior of the optimization procedure. Effects of pork price on optimal strategies were investigated using three different price scenarios: low (1.173 €/kg), medium (1.314 €/kg), and high (1.662 €/kg) pork prices. Optimizing only feeding strategies improved the gross margin per pig by 5.0% while optimizing shipping strategies improved the mean gross margin per pig by 4.7%. Optimizing both feeding and shipping strategies improved the gross margin per fattened pig by 10% (2.88 €/pig, with medium pork price (1.314€/kg)) compared to the common practice on farms in France. Pork price had a limited effect on feeding decisions when optimized alone, but a strong impact on shipping decisions. Economic optimization of pig fattening inconsistently affected the environmental impacts. However, increasing pork price improved the optimized mean gross margin per pig but increased all environmental impacts. To our knowledge, this is the first tool able to optimize both feeding and shipping strategies while considering effects of variability in growth potential among a batch of pigs. These features allow consideration of the interaction effect of feeding and shipping strategies on the economic outputs of the batch, and investigation of the trade-off between production cost and technical performance. This tool should interest the pig sector since it can identify the best feeding and shipping strategies depending on the economic context. Further work should consider multiobjective optimization with both economic and environmental objectives.