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An Effective Hybrid Cuckoo Search Algorithm with Improved Shuffled Frog Leaping Algorithm for 0-1 Knapsack Problems

机译:一种改进的改进蛙跳算法的混合杜鹃搜索算法解决0-1背包问题

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摘要

An effective hybrid cuckoo search algorithm (CS) with improved shuffled frog-leaping algorithm (ISFLA) is put forward for solving 0-1 knapsack problem. First of all, with the framework of SFLA, an improved frog-leap operator is designed with the effect of the global optimal information on the frog leaping and information exchange between frog individuals combined with genetic mutation with a small probability. Subsequently, in order to improve the convergence speed and enhance the exploitation ability, a novel CS model is proposed with considering the specific advantages of Lévy flights and frog-leap operator. Furthermore, the greedy transform method is used to repair the infeasible solution and optimize the feasible solution. Finally, numerical simulations are carried out on six different types of 0-1 knapsack instances, and the comparative results have shown the effectiveness of the proposed algorithm and its ability to achieve good quality solutions, which outperforms the binary cuckoo search, the binary differential evolution, and the genetic algorithm.
机译:提出了一种有效的混合布谷鸟搜索算法(CS),该算法具有改进的随机蛙跳算法(ISFLA),用于解决0-1背包问题。首先,在SFLA框架下,设计了一种改进的蛙跳算子,其具有全局最优信息,对蛙跳和蛙个体之间的信息交换以及遗传突变相结合的可能性很小。随后,为了提高收敛速度并提高开发能力,考虑到Lévy航班和蛙跳算子的特殊优点,提出了一种新颖的CS模型。此外,贪婪变换方法用于修复不可行解并优化可行解。最后,对六种不同类型的0-1背包实例进行了数值模拟,比较结果表明了该算法的有效性及其实现优质解的能力,其性能优于二元布谷鸟搜索,二元差分进化。 ,以及遗传算法。

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