Março 2021 vol. 7 num. 1 - XI Encontro Científico de Física Aplicada

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A comparative study of gradient-based and meta-heuristic optimization methods using Griewank benchmark function

A comparative study of gradient-based and meta-heuristic optimization methods using Griewank benchmark function

Dalla, C. E. R ; da Silva, W. B. ; Dutra, J. C. S. ; Colaço, J. M. ; , ;

Artigo completo:

Optimization methods are frequently applied to solve real-world problems such, engineering design, computer science, and computational chemistry. This paper aims to compare gradient-based algorithms and the meta-heuristic particle swarm optimization to minimize the multidimensional benchmark Griewank function, a multimodal function with widespread local minima. Several approaches of gradient-based methods such as steepest descent, conjugate gradient with Fletcher-Reeves and Polak- Ribiere formulations, and quasi-Newton Davidon-Fletcher-Powell approach were compared. The results presented showed that the meta-heuristic method is recommended for function with this behavior because is no needed prior information of the search space. The performance comparison includes computation time and convergence of global and local optimum.

Artigo completo:

Optimization methods are frequently applied to solve real-world problems such, engineering design, computer science, and computational chemistry. This paper aims to compare gradient-based algorithms and the meta-heuristic particle swarm optimization to minimize the multidimensional benchmark Griewank function, a multimodal function with widespread local minima. Several approaches of gradient-based methods such as steepest descent, conjugate gradient with Fletcher-Reeves and Polak- Ribiere formulations, and quasi-Newton Davidon-Fletcher-Powell approach were compared. The results presented showed that the meta-heuristic method is recommended for function with this behavior because is no needed prior information of the search space. The performance comparison includes computation time and convergence of global and local optimum.

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DOI: 10.5151/xiecfa-Dalla

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Como citar:

Dalla, C. E. R; da Silva, W. B.; Dutra, J. C. S.; Colaço, J. M.; , ; "A comparative study of gradient-based and meta-heuristic optimization methods using Griewank benchmark function", p. 156-160 . In: Anais do XI Encontro Científico de Física Aplicada. São Paulo: Blucher, 2021.
ISSN 2358-2359, DOI 10.5151/xiecfa-Dalla

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