中文摘要：

研究了遗传算法中的位重要性和位收敛顺序性,给出了重要位、模式、参数区间和目标函数四者之间的关系,提出了一种新的进化算法——位重要性进化算法（Bit Importance Evolutionary Algorithm,BIEA）.BIEA通过检测组成个体各位的重要性,对于重要位,加快其收敛;对于非重要位,保持其多样性.数据实验表明：BIEA在收敛速度上要优于遗传算法,同时BIEA也可以有效地解决一类遗传算法很难解决的强欺骗性问题.

英文摘要：

The bit importance and convergent order of bit in genetic algorithms （GA） are studied. Relationships among important bits, schema, parameter range and target function are presented,and then a novel evolutionary algorithm, called Bit Importance Evolutionary Algorithm （BIEA） is proposed. BIEA detects the important bits in a chromosome at first, and then speeds up the convergence of important bits, while maintaining the diversity of unimportant bits. Numerical experiments show that compared with GA, BIEA has a better convergent velocity and can solve some hard deceptive problems which can＇t be solved effectively by GA.