机构综合的混沌搜索自适应入侵遗传算法研究

Adaptive invading genetic algorithm based on chaos search and its application to mechanism synthesis

将生物系统中"入侵"的概念引入遗传算法,提出机构综合排斥二周期点优化求解的一种基于混沌搜索自适应入侵遗传算法。该算法动态地引入入侵种群,并利用混沌搜索产生入侵个体。入侵种群的扩散使优良基因得以在个体中传播,优化了种群的基因构成,能够促使种群跳出局部最小,并向全局优化方向进化,从而有效避免了遗传算法的早熟现象。将该算法应用排斥二周期点优化求解,实例表明该算法具有较快的收敛速度和较强的寻优能力,能够快速求出机构综合问题非线性方程组全部解。

By introducing the concept of invasion of biological systems into Genetic Algorithm（GA） ,a chaos search for the optimum solution of repulsion two-cycle point of mechanism synthesis based Adaptive Invading Genetic Algorithm （AIGA） was proposed. The invading population, whose size was dynamically determined, was obtained through Chaos Search （CS）. The expansion of the invading population was capable of propagating excellent genes among individuals and optimizing the gene structure of the population. And thus, it made the population evolve towards the global optimum. As a result, the algorithm was able to diminish the probability of being convergent to local minima prematurely. The proposed algorithm was applied to the repulsion two-cycle point function optimization. And the mechanism synthesis results show that this algorithm has the merits of fast convergence and global optimization and can find all solutions of the nonlinear equations for mechanism synthesis nonlinear questions.