These subproblems are optimised separately while exchanging information in order to solve the complete problem.
The nature of the embedded optimisation algorithm determines whether C3's behaviour is deterministic or stochastic.
This makes C3iDE very effective on large-scale global optimisation problems (up to 1000 dimensions) compared to cooperative coevolutionary algorithm (CC) and Differential evolution.
Phase II, and thereby the current iteration, are terminated when the search of the CC algorithm stagnates and no significantly better solutions are being found.
The algorithm again starts with the advanced constructive initial optimisations of the subpopulations, considering an increasing subset of subproblems.
During these initial optimisations, the subpopulation of the latest included subproblem is evolved by a multi-objective evolutionary algorithm.
The constructive cooperative coevolution algorithm has been applied to different types of problems, e.g. a set of standard benchmark functions,[4][6] optimisation of sheet metal press lines[4][5] and interacting production stations.