纺织高校基础科学学报2018，Vol.31Issue(1)：108-114,7.DOI:10.13338/j.issn.1006-8341.2018.01.018
一种基于权重策略的蝙蝠算法
A bat algorithm based on weighted strategy
摘要
Abstract
In view of the shortcomings of the bat algorithm,such as slow convergence rate,easy to fall into local extremum and poor stability,a bat algorithm based on weighted strategy is presented.The weighted strategy is introduced in the bats learning mechanism for no longer learning from the global optimal bat,but sharing and exchanging information with all the bats in the neighborhood,and adaptively adjusts the force of learning from other bats to optimize the iterative population,increase the diversity of the population,and effectively improve the global search ability and search precision of the algorithm.The numerical results show that the new algorithm has faster convergence speed and higher optimization accuracy.关键词
蝙蝠算法/权重策略/自适应学习/算法性能Key words
bat algorithm/weighted strategy/adaptive learning/algorithm performance分类
信息技术与安全科学引用本文复制引用
郭旭,贺兴时,高昂..一种基于权重策略的蝙蝠算法[J].纺织高校基础科学学报,2018,31(1):108-114,7.基金项目
西安市教育科技重大招标项目(2015ZB-ZY04) （2015ZB-ZY04）
陕西省软科学研究计划项目(2014KRM2801) （2014KRM2801）
