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

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