中文摘要：

由于遗传算法具有较强的全局搜索能力,但在实际应用中容易产生早熟收敛现象,且进化后期搜索效率较低,而大洪水演算法是求解组合优化问题的独特算法,结合两者的优点,形成基于遗传算法的大洪水演算法（Genetic Great Deluge Algorithm,GGDA）,然后应用该混合算法求解不同规模的多维背包问题（Multidimensional Knapsack Problem,MKP）,求解结果表明提出的算法是简单有效的,优于标准遗传算法和大洪水演算法。

英文摘要：

The Genetic Algorithm（ GA） has better global search ability,but is easily prone to have premature convergence phenomenon in the practical application,with the low search efficiency in late evolution,while the Great Deluge Algorithm（ GDA） is a unique algorithm for solving combinatorial optimization problems. Combined the advantages of the both algorithms,we form the genetic great deluge algorithm（ GGDA）,and then apply the hybrid algorithm to solve different scales of Multidimensional Knapsack Problem（ MKP）. The results show that the hybrid algorithm is simple and effective,superior to the standard GA and the GDA.