Frequent decoding operations severely reduce the optimization efficiency when the binary Quantum Genetic Algorithm(QGA) based on qubits measure is applied to the continuous space optimization.
利用基于量子位测量的二进制量子遗传算法(QGA)对连续问题进行优化时，频繁的解码运算严重降低了优化效率。
参考来源 - 基于改进QGA的T·2,447,543篇论文数据，部分数据来源于NoteExpress
这种改进的量子遗传算法采用了已搜索到的最佳个体更新量子门和群体灾变策略。
In IQGA, the strategies of updating quantum gate using the best solution obtained and population catastrophe were adopted.
对典型函数测试表明：该方法有效地提高了量子遗传算法的计算精度和收敛速度。
The results of testing typical function demonstrate that the precision and the rate of convergence are improved by FQGA.
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