改进进化方向的量子遗传算法  

Quantum Genetic Algorithm Based on Improved Evolutionary Direction

作　　者：安秀芳[1] 

机构地区：[1]徐州工业职业技术学院信息与电气工程学院,江苏徐州221400

出　　处：《实验室研究与探索》2017年第12期61-64,77,共5页Research and Exploration In Laboratory

摘　　要：为提高量子遗传算法的全局搜索速度和精度,提出改进进化方向的量子遗传算法(QGAIED)。该方法通过计算优化方向和参照当前全局最优解,实现了进化步长的自适应调整。在步长的调整过程中,QGAIED通过权值同时控制两个优化方向,在保证全局搜索能力的同时也提高了搜索速度。将该方法应用于数学优化和工程优化,结果表明,该方法能够快速准确的寻找到全局最优解。In order to increase searching speed and precision of quantum genetic algorithm, the quantum genetic algorithm based on improved evolutionary direction（QGAIED） is proposed. In the algorithm the evolutionary step size is adjusted by computing optimization direction,and combining with present globally optimal solution. During the progress of adjusting step size, two optimization directions are simultaneously controlled by the weight. Thus,the globally searching ability is ensured, and the searching speed is improved. QGAIED is applied to solve mathematical optimization problem and engineering optimization problem, the results show that it can quickly and correctly find globally optimal solution.

关 键 词：优化算法 量子遗传算法 步长 进化方向 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]