中文说明：洗牌的飞跃青蛙算法 （样图） 是新自然启发智能算法利用整个的更新和评价战略解决方案。求解多维函数优化问题，这一战略将会恶化的收敛速度和算法由于维度之间的干涉现象的解决方案的质量。为了克服这方面的不足，提出了基于样图的维度的维度改进。拟议的战略结合到其他维度值更新后的值的一维将贪婪地接受新的解决方案，而且其更新后的值可以完善的解决方案。此外，新的个别更新配方，旨在同时学习经验既从全局和局部最优解。同时，他们还彰显改性算法是竞争相比其他一些改进算法的连续函数优化问题。
English Description：
Shuffled leap frog algorithm (SFLA) is a new nature-inspired intelligent algorithm, which uses the whole update and evaluation strategy on solutions. For solving multi-dimension function optimization problems, this strategy will deteriorate the convergence speed and the quality of solution of algorithm due to interference phenomena among dimensions. To overcome this shortage, a dimension by dimension improvement based on SFLA is proposed. The proposed strategy combines an updated value of one dimension with values of other dimensions into a new solution, and that whose updated value can improve the solution will be accepted greedily. Further, a new individual update formula is designed to learn experiences both from the global best and the local best solution simultaneously. Meanwhile, they also reveal the modified algorithm is competitive for continuous function optimization problems compared with other improved algorithms.