Title: A new hybrid algorithm for unconstrained optimisation problems

Authors: Jida Huang; Xinyu Li; Liang Gao

Addresses: State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China ' State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China ' State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

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 Lévy 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.

Keywords: cuckoo search; teaching-learning based optimisation; TLBO; hybrid algorithms; unconstrained optimisation.

DOI: 10.1504/IJCAT.2013.052808

International Journal of Computer Applications in Technology, 2013 Vol.46 No.3, pp.187 - 194

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 23 Mar 2013 *

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