Abstract
A new optimisation algorithm which hybridises cuckoo search CS with teaching-learning-based optimisation TLBO is proposed for solving unconstrained optimisation problems. The new algorithm involves the concept of Levy flight of the solutions and the information exchange based on teaching-learning process between the best solutions. The proposed method, combining the advantage of CS and TLBO, can strengthen the local search ability and accelerate the convergence rate. The effectiveness and performance of the method is evaluated on several large scale non-linear benchmark functions with different characteristics, and the results are compared with CS and TLBO. The experimental results show that the proposed algorithm outperforms other two algorithms and has achieved satisfactory improvement.
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