CAJ | 학술논문

针对标准遗传算法的局部搜索能力差、解的精度低等一些不足，提出了一种嵌入演化策略的双种群遗传算法，即用自适应遗传算法进行大种群寻优，用演化策略优化小种群。将该方法应用于非线性约束优化问题中，结果表明，该算法的局部搜索能力、精度和计算速度较改进前有明显提高。
침대표준유전산법적국부수색능력차、해적정도저등일사불족，제출료일충감입연화책략적쌍충군유전산법，즉용자괄응유전산법진행대충군심우，용연화책략우화소충군。장해방법응용우비선성약속우화문제중，결과표명，해산법적국부수색능력、정도화계산속도교개진전유명현제고。
Because of the weak capability in local search and the lack of precision in the standard Genetic Algorithm(GA), a new algorithm —— the Dual Population Genetic Algorithm embedded in Evolution Strategies(ESs) —— is proposed. This algorithm is used to optimize toward the general population with a self-adaptive GA and to look for toward the local population with Evolution Strategies. This algorithm is applied to nonlinear optimization problems with restraining conditions and the results show that the ability in local research, the precision of the calculation speed and its speed are greatly improved.