Constructive cooperative coevolution for large-scale global optimisation
提出了一种名为C3的构造性协同协同进化算法，通过多起点架构和构造性启发式方法生成初始可行解，在CEC'2013测试集上对高维问题表现优异，尤其适用于部分可分和重叠函数。
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.