Comparison of Cuckoo Search, Tabu Search and TS-Simplex algorithms for unconstrained global optimization

Ghania Khensous (1) , Belhadri Messabih (1) , Abdellah Chouarfia (1) , Bernard Maigret (2)

1 USTO MB - Université des sciences et de la Technologie d'Oran Mohamed Boudiaf [Oran]
2 CAPSID - Computational Algorithms for Protein Structures and Interactions

Metaheuristics Algorithms are widely recognized as one of the most practical approaches for Global Optimization Problems. This paper presents a comparison between two metaheuristics to optimize a set of eight standard benchmark functions. Among the most representative single solution metaheuristics, we selected Tabu Search Algorithm (TSA), to compare with a novel population-based metaheuristic: Cuckoo Search Algorithm (CSA). Empirical results reveal that the problem solving success of the TSA was better than the CSA. However, the run-time complexity for acquiring global minimizer by the Cuckoo Search was generally smaller than the Tabu Search. Besides, the hybrid TSA-Simplex Algorithm gave superior results in term of efficiency and run-time complexity compared to CSA or TSA tested alone.

Mots clés: Nature Inspired Algorithms; Global Optimization; CSA; Metaheuristic Algorithms; TSA

Domaines: Bio-informatique [q-bio.QM]

Ghania Khensous, Belhadri Messabih, Abdellah Chouarfia, Bernard Maigret. Comparison of Cuckoo Search, Tabu Search and TS-Simplex algorithms for unconstrained global optimization. Computer Modelling and New Technologies, 2016, 20 (4), pp.23-29. ⟨hal-01537775⟩