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Computational Intelligence and Neuroscience
Volume 2014 (2014), Article ID 857254, 17 pages
Research Article

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

1School of Information Engineering, Shijiazhuang University of Economics, Shijiazhuang 050031, China
2School of Computer Science and Technology, Jiangsu Normal University, Xuzhou, Jiangsu 221116, China
3School of Mathematical Science, Kaili University, Kaili, Guizhou 556011, China

Received 4 June 2014; Revised 13 September 2014; Accepted 14 September 2014; Published 22 October 2014

Academic Editor: Saeid Sanei

Copyright © 2014 Yanhong Feng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.