中文摘要：

混合蛙跳算法（SFLA）是一种全新的后启发式群体进化算法，具有高效的计算性能和优良的全局搜索能力。背包问题是一个典型的NP完全问题。首先建立了背包问题基于0／1规划的数学模型，阐述了混合蛙跳算法的基本理论。针对离散搜索空间，提出了SFLA的改进算法，应用该算法解决了背包问题。在实例上的运行结果表明本文方法的可行性和有效性。

英文摘要：

Shuffled Frog Leaping Algorithm （SFLA） is a new meta-heuristic population evolutionary algorithm. It has fast calculation speed and excellent global search capability. Knapsack problem is a typical NP-eomplete problem. The 0-1 Knapsack problem mathematical model is established first, then the basic principle of SFLA is introduced. Aim at searching in discrete search space, an improved SFLA algorithm is given. And then, it is used to solve Knapsack problem. The results got on some typical instances show that the proposed method is feasible and effective.