摘要： 为了加快进化算法中种群的寻优速度，设计双变异算子，提出一种进化算法。该算法以种群的多样性、算法的收敛速度、全局与局部搜索能力的综合均衡为设计重点，利用概率论和Markov链证明了该算法的全局收敛性，通过对6个基准函数进行测试，从数值上验证了该算法的有效性。

关键词: 全局优化, 进化算法, 全局收敛性

Abstract: To increase the speed of finding the optima in evolutionary algorithms, two mutation operators are designed, and a new evolutionary algorithm based on them is proposed. The algorithm emphasizes the population diversity, the convergence speed, the balance of global search ability and local search ability. Its global convergence is proved by the theories of probability and Markov chain. The test results of six benchmark functions indicate the algorithm improves the performance effectively.

Key words: global optimization, evolutionary algorithm, global convergence

中图分类号: 

• TP18