Abstract: There are many different operators in evolutionary algorithms. Each operator has been applied successfully in solving some optimization problems, however not efficiently in other problems. A novel improved multi-operator evolutionary algorithm based on communication is proposed. In the algorithm, two subgroups are parallel performed with the different operators: multi-parent crossover operator and Cauchy mutation operator. The individual, together with information, is exchanged while subgroup is reorganized. The new algorithm is tested on 23 benchmark functions. Simulation results have shown that this algorithm can solve all test functions very well and its performance is the same as or even better than the best of pure operator does.

Key words: evolutionary algorithm, communication, multi-parent crossover, Cauchy mutation

摘要： 演化算法中有很多不同的演化算子，每一种算子对于不同的优化问题都有自己的优点和缺点。本文提出了一种基于交流模型的多算子混合演化算法。在该算法中，有两个种群，使用两种算子：多父体杂交算子和Cauchy变异算子。种群间的信息交换通过个体交流实现。对23个标准测试函数的数值仿真表明，该算法具有良好的全局收敛性和鲁棒性。

关键词: 演化算法, 交流, 多父体杂交, Cauchy变异