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Shuffled Complex-Self Adaptive Hybrid Evolution (Sc-Sahel) Optimization Framework, Mojtaba Sadegh
Shuffled Complex-Self Adaptive Hybrid Evolution (Sc-Sahel) Optimization Framework, Mojtaba Sadegh
Civil Engineering Faculty Publications and Presentations
Simplicity and flexibility of meta-heuristic optimization algorithms have attracted lots of attention in the field of optimization. Different optimization methods, however, hold algorithm-specific strengths and limitations, and selecting the best-performing algorithm for a specific problem is a tedious task. We introduce a new hybrid optimization framework, entitled Shuffled Complex-Self Adaptive Hybrid EvoLution (SC-SAHEL), which combines the strengths of different evolutionary algorithms (EAs) in a parallel computing scheme. SC-SAHEL explores performance of different EAs, such as the capability to escape local attractions, speed, convergence, etc., during population evolution as each individual EA suits differently to various response surfaces. The SC-SAHEL algorithm …