摘要
为提高混合蛙跳算法在求解高维复杂函数和离散优化问题的性能,提出一种离散混合蛙跳算法.首先,引入扰动系数来调控青蛙个体的移动距离,从而更好的平衡迭代中算法的全局探索和局部开发能力;其次,利用螺旋更新位置策略使算法能够在最优解附近进行更加精细的搜索;同时,采用随机搜索策略,提高算法的全局搜索能力;另外,通过借鉴2-opt方法,实现全局最优解变异,丰富种群的多样性;最后,利用改进的Sigmoid函数对个体位置进行离散化处理.通过对9个典型的基准函数和油田措施规划方案的仿真实验表明,相较于对比的算法,DSFLA的收敛精度和寻优速度有明显的提升.
A shuffled frog leaping algorithm is proposed to overcome the defects of fall into local optimum easily and the lack of ability to solve discrete optimization problems when solving high-dimensional complex problems.In the proposed algorithm,using the perturbation coefficient to regulate the movement of individual frog distance,so as to better balance the global search and local development capabilities of the algorithm;using the spiral update position strategy to enable the algorithm to perform a more comprehensive and refined search near the optimal solution;using a random search strategy to improve the global search ability of the algorithm;using the 2-opt method to implement the global optimal solution mutation to increase the diversity of the population;the SFLA algorithm is discretized by the improved Sigmoid function.The optimization experiments are conducted on the 9 benchmark functions and oilfield measures planning.Simulation results show that the proposed DSFLA has a better search performance.
作者
张强
郭玉洁
ZHANG Qiang;GUO Yu-Jie(School of Computer and Information Technology,Northeast Petroleum University,Daqing 163318,China)
出处
《计算机系统应用》
2020年第12期144-153,共10页
Computer Systems & Applications
基金
国家自然科学基金(61702093)
黑龙江省自然科学基金(F2018003)
作者简介
通讯作者:郭玉洁,E-mail:gyujieii@126.com
