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A recent nature inspired optimization algorithm, Fish School Search (FSS) is applied to the finite element model (FEM) updating problem. This method is tested on a GARTEUR SM-AG19 aeroplane structure. The results of this algorithm are compared with two other metaheuristic algorithms, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). It is observed that on average, the FSS and PSO algorithms...
This work delves into variations of FSS that uses local information (i.e. fish weights) for splitting the school and presents comparative analyses of the new method, tried here in three ways. Hence, this is an attempt to create a more economical alternative for the best performing multimodal version of the algorithm FSS, the dFSS. The work capitalizes on some modifications in the Collective Instinctive...
Fish School Search (FSS) is swarm-based optimizer that excels on multimodal search problems, but presents some drawbacks, such as the necessity to proper define the step used in some operators and the need to evaluate the fitness function twice per fish per iteration. This paper presents a simpler and enhanced version of the FSS, that features three advantages over the original FSS: high exploitation...
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