Constructive cooperative coevolution for large-scale global optimisation

This paper presents the Constructive Cooperative Coevolutionary (\(\mathrm {C}^3\)) algorithm, applied to continuous large-scale global optimisation problems. The novelty of \(\mathrm {C}^3\) is that it utilises a multi-start architecture and incorporates the Cooperative Coevolutionary algorithm. The considered optimisation problem is decomposed into subproblems. An embedded optimisation algorithm optimises the subproblems separately while exchanging information to co-adapt the solutions for the subproblems. Further, \(\mathrm {C}^3\) includes a novel constructive heuristic that generates different feasible solutions for the entire problem and thereby expedites the search. In this work, two different versions of \(\mathrm {C}^3\) are evaluated on high-dimensional benchmark problems, including the CEC’2013 test suite for large-scale global optimisation. \(\mathrm {C}^3\) is compared with several state-of-the-art algorithms, which shows that \(\mathrm {C}^3\) is among the most competitive algorithms. \(\mathrm {C}^3\) outperforms the other algorithms for most partially separable functions and overlapping functions. This shows that \(\mathrm {C}^3\) is an effective algorithm for large-scale global optimisation. This paper demonstrates the enhanced performance by using constructive heuristics for generating initial feasible solutions for Cooperative Coevolutionary algorithms in a multi-start framework.