Fitness functions for low-dimensional parts of cooperative coevolution algorithms
Every sub-vector is evaluated by concatenating it with the best-fit individuals (sub-vectors) from the rest of the sub-populations to form a so called context vector.

The context vector contains all the parameters required by the benchmark function and is fed into it for fitness evaluation.

This is actually where the cooperation happens.

DECC-G is "just" a cooperative co-evolutionary (CC) scheme based on Differential Evolution (DE) and a random split/grouping of the vectors/individuals (-G).

It shares with the other co-evolutionary algorithms the general architecture:


(Coevolutionary model of three species shown from the perspective of each in turn. Image from Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents by Mitchell A. Potter, Kenneth A. De Jong)



As a side note the reference implementation of DECC-G can be found here.