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A hybrid meta-heuristic for global optimisation using low-discrepancy sequences of points

<12>This paper investigates a new global optimization conceptual approach by incorporating so called Low-Discrepancy sequences into a novel hybrid meta-heuristic method. It exploits initial uniform search of the parameter space and meta-heuristic knowledge to guide the search, and subsequently, a simplex local optimizer to refine the solution. Tests results are compared with other state-of-the-art GO techniques, showing superiority in terms of efficiency and success rate. The significance of this work is in proposing a novel, efficient and accurate method for GO. Because of its novelty and originality it was included as ‘original research article’ in a special issue “Hybrid Metaheuristics”.