In this article we present an evolutionary algorithm for the optimization of sequences of targets for the multitarget regression algorithm Ensemble of Regressor Chains. This algorithm selects several random sequences or chains of targets where to predict each target, the values of previous targets in the chain are included as features, considering in this way the relationship among them. Under the assumption that a target may be better predicted if it is highly correlated with the targets which were included as feature, our proposal, called CCOERC, looks for chains where each target is highly correlated with previous targets in the chain. Several methods for the combination of predictions in the ensemble and for the selection of the chains which forms the ensemble are also proposed. CCOERC is compared to other state-of-the-art algorithms in multitarget regression, presenting statistically better performance than them.
