计算机工程与应用2019，Vol.55Issue(7)：48-52,187,6.DOI:10.3778/j.issn.1002-8331.1805-0421
修正浓度与适应步长的果蝇优化算法
Fruit Fly Optimization Algorithm with Modified Concentration and Adaptive Step
摘要
Abstract
The basic fruit fly optimization algorithm can only be positive when solving the optimization problem, and it can not optimize the problem when the concentration is negative. In addition, the step size of the basic fruit fly optimization algorithm is random in iterative optimization, which makes the algorithm precocious and fall into the local optimal solution, and the accuracy of the algorithm is not high. Aiming at these problems of the basic fruit fly algorithm, a modified concen-tration and adaptive step algorithm for fruit fly is proposed. This algorithm modifies the concentration of fruit fly and makes the taste concentration distribution in the whole range of positive and negative optimization. In iteration, the search distance of fruit fly is changed adaptively by making full use of the global factors that have been carried out in fruit fly population. In order to verify the effectiveness of the algorithm, several commonly used test functions are selected to verify the algorithm. The results show that the algorithm can not only effectively avoid falling into local optimum, but also improve the precision of optimization.关键词
果蝇优化算法/修正浓度/适应步长/局部最优/寻优精度Key words
fruit fly optimization algorithm/modified concentration/adaptive step/local optimum/precision of optimization分类
信息技术与安全科学引用本文复制引用
信成涛,邹海..修正浓度与适应步长的果蝇优化算法[J].计算机工程与应用,2019,55(7):48-52,187,6.基金项目
国家自然科学基金(No.61672124,No.61370145,No.61173183) （No.61672124,No.61370145,No.61173183）
"十三五"国家密码发展基金密码理论研究课题(No. MMJJ20170203). （No. MMJJ20170203）
