Swarm intelligence
On the performance of artificial bee colony (ABC) algorithm
Applied Soft Computing
Journal of Global Optimization
Harmony search based algorithms for bandwidth-delay-constrained least-cost multicast routing
Computer Communications
Modified Harmony Search Methods for Uni-Modal and Multi-Modal Optimization
HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems
Learning algorithm for multimodal optimization
Computers & Mathematics with Applications
An Improved Harmony Search Algorithm with Differential Mutation Operator
Fundamenta Informaticae - Swarm Intelligence
Harmony search algorithm for solving Sudoku
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Chaotic bee colony algorithms for global numerical optimization
Expert Systems with Applications: An International Journal
The improvement of glowworm swarm optimization for continuous optimization problems
Expert Systems with Applications: An International Journal
Computational Optimization and Applications
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Harmony search (HS) is one of the newest and the easiest to code music inspired heuristics for optimization problems. In order to enhance the accuracy and convergence rate of harmony search, a hybrid harmony search is proposed by incorporating the artificial bee colony algorithm (ABC). The artificial bee colony algorithm is a new swarm intelligence technique inspired by intelligent foraging behavior of honey bees. The ABC and its variants are used to improve harmony memory (HM). To compare and analyze the performance of our proposed hybrid algorithms, a number of experiments are carried out on a set of well-known benchmark global optimization problems. The effects of the parameters about the hybrid algorithms are discussed by a uniform design experiment. Numerical results show that the proposed algorithms can find better solutions when compared to HS and other heuristic algorithms and are powerful search algorithms for various global optimization problems.