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A mixed algorithm for smooth global optimization | ||
| Journal of Mathematical Modeling | ||
| مقاله 1، دوره 11، شماره 2، مهر 2023، صفحه 207-228 اصل مقاله (5.99 M) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22124/jmm.2022.23133.2061 | ||
| نویسندگان | ||
| Raouf Ziadi* ؛ Abdelatif Bencherif-Madani | ||
| Laboratory of Fundamental and Numerical Mathematics (LMFN), Department of Mathematics, University Ferhat Abbas Setif 1, 19000 Setif, Algeria | ||
| چکیده | ||
| This paper presents a covering algorithm for solving bound-constrained global minimization problems with a differentiable cost function. In the proposed algorithm, we suggest to explore the feasible domain using a one-dimensional global search algorithm through a number of parametric curves that are relatively spread and simultaneously scan the search space. To accelerate the corresponding algorithm, we incorporate a multivariate quasi-Newton local search algorithm to spot the lowest regions. The proposed algorithm converges in a finite number of iterations to an $\varepsilon$-approximation of the global minimum. The performance of the algorithm is demonstrated through numerical experiments on some typical test functions. | ||
| کلیدواژه‌ها | ||
| Global optimization؛ Alienor dimensionality reduction technique؛ One-dimensional global search algorithm؛ Limited Memory BFGS-B algorithm | ||
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آمار تعداد مشاهده مقاله: 390 تعداد دریافت فایل اصل مقاله: 720 |
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