摘要
针对目前交互式遗传算法由于使用小规模的种群和较少的进化代数,容易导致算法的搜索能力有限、易陷入局部优化的问题,在引入一种加速收敛变异策略的基础上,提出一种新的交互式遗传算法。给出了算法设计实施中关键问题的处理,分析了算法的效率,并通过函数优化和服装设计问题的仿真实验验证变异策略和算法的有效性。
Based on introduction of a novel mutation strategy, a new interactive genetic algorithm was proposed aiming on inefficient searching ability and local optimization of current interactive genetic algorithm caused by using a small population size and a few generations. The issues to implement were proposed, The efficiency of the proposed algorithm was analyzed. The simulation of function optimization and fashion design indicates the mutation strategy and the algorithm is effective.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2007年第9期1913-1916,共4页
Journal of System Simulation
基金
国家自然科学基金(70471046)
高等学校博士学科点专项科研基金(20050359006
20040359004)
安徽省自然科学基金(070416243)
关键词
交互式遗传算法
变异
用户疲劳
服装设计
interactive genetic algorithm
mutation
human fatigue
fashion design
