Cooperative coevolutionary algorithms (CCEAs) divide a given problem in to a number of subproblems and use an evolutionary algorithm to solve each subproblem. This letter is concerned with the scenario under which a single fitness measure exists. By removing the typically used subproblem partnering mechanism, it is suggested that such CCEAs can be viewed as making use of a generalized version of the global crossover operator introduced in early evolution strategies. Using the well-known NK model of fitness landscapes, the effects of varying aspects of global crossover with respect to the ruggedness of the underlying fitness landscape are explored. Results suggest improvements over the most widely used form of CCEAs, something further demonstrated using other well-known test functions.

中文翻译：

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论协同进化与全局交叉

合作协同进化算法（CCEA）将给定问题划分为多个子问题，并使用进化算法来解决每个子问题。这封信涉及的是存在单一适应度测量的情况。通过删除通常使用的子问题合作机制，建议此类 CCEA 可以被视为利用早期演化策略中引入的全局交叉算子的通用版本。使用著名的适应度景观 NK 模型，探讨了全局交叉的不同方面对潜在适应度景观的崎岖性的影响。结果表明，对最广泛使用的 CCEA 形式进行了改进，使用其他众所周知的测试函数进一步证明了这一点。