计算机应用研究2013，Vol.30Issue(3)：760-763,4.DOI:10.3969/j.issn.1001-3695.2013.03.030
改进的反向蛙跳算法求解函数优化问题
Improved opposition-based shuffled frog leaping algorithm for function optimization problems
摘要
Abstract
Classical shuffled frog leaping algorithm is slow in convergence, and has a low convergent precision to address continuous function optimization problems. To overcome such shortages, this paper presented an improved shuffled frog leaping algorithm which combined the OBL strategy. The proposed approach employed OBL for population initialization and generation jumping to produce populations closer to high-quality solutions. The experiments carried on classic benchmark functions show that it performs significantly better both in terms of convergence speed and solution precision.关键词
混洗蛙跳算法/反向学习/函数优化Key words
shuffled frog leaping algorithm(SFLA) / opposition-based learning( OBL) / function optimization分类
信息技术与安全科学引用本文复制引用
林娟,钟一文,马森林..改进的反向蛙跳算法求解函数优化问题[J].计算机应用研究,2013,30(3):760-763,4.基金项目
福建省教育厅科技研究项目(JB09113) （JB09113）
福建农林大学青年教师科研基金资助项目(2010018) （2010018）
