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A mixed algorithm for smooth global optimization | ||
Journal of Mathematical Modeling | ||
مقالات آماده انتشار، اصلاح شده برای چاپ، انتشار آنلاین از تاریخ 12 بهمن 1401 اصل مقاله (5.99 M) | ||
نوع مقاله: Research Article | ||
شناسه دیجیتال (DOI): 10.22124/jmm.2022.23133.2061 | ||
نویسندگان | ||
Raouf Ziadi ![]() ![]() | ||
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 | ||
آمار تعداد مشاهده مقاله: 66 تعداد دریافت فایل اصل مقاله: 124 |