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Titlebook: Advances in Metaheuristic Algorithms for Optimal Design of Structures; Ali Kaveh Book 2021Latest edition The Editor(s) (if applicable) and

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21#
發(fā)表于 2025-3-25 06:01:37 | 只看該作者
22#
發(fā)表于 2025-3-25 10:42:58 | 只看該作者
Victoria Abou-Khalil,Hiroaki Ogataf these optimization methods is to efficiently explore the search space in order to find global or near-global solutions. Since they are not problem specific and do not require the derivatives of the objective function, they have received increasing attention from both academia and industry.
23#
發(fā)表于 2025-3-25 14:15:41 | 只看該作者
Shogo Taniguchi,Takashi Yoshinoering. These methods, which are usually inspired by natural phenomena, do not require any gradient information of the involved functions and are generally independent of the quality of the starting points. As a result, metaheuristic optimizers are favorable choices when dealing with discontinuous, m
24#
發(fā)表于 2025-3-25 18:50:27 | 只看該作者
Masanori Yamada,Kosuke Kaneko,Yoshiko Godasearch space and require the control of a great number of design constraints. Separate design decisions for each variable would be allowed. Thus, the optimizer invoked to process such a sizing problem is given the possibility to really optimize the objective function by detecting the optimum solutio
25#
發(fā)表于 2025-3-25 22:14:12 | 只看該作者
Lecture Notes in Computer ScienceThis chapter consists of two parts. In first part, the standard Magnetic Charged System Search (MCSS) is presented and applied to different numerical examples to examine the efficiency of this algorithm. The results are compared to those of the original charged system search method [.].
26#
發(fā)表于 2025-3-26 01:37:46 | 只看該作者
Lecture Notes in Computer ScienceAlthough different metaheuristic algorithms have some differences in approaches to determine the optimum solution, however their general performance is approximately the same.
27#
發(fā)表于 2025-3-26 06:16:32 | 只看該作者
Detection of Football Spoilers on TwitterThe Big Bang-Big Crunch (BB–BC) method developed by Erol and Eksin (Adv Eng Softw 37:106–111, 2006 [.]) consists of two phases: a Big Bang phase, and a Big Crunch phase. In the Big Bang phase, candidate solutions are randomly distributed over the search space.
28#
發(fā)表于 2025-3-26 09:37:02 | 只看該作者
29#
發(fā)表于 2025-3-26 14:48:36 | 只看該作者
Detection of Football Spoilers on TwitterColliding bodies optimization (CBO), was employed for size optimization of skeletal structures in Chap. 7.
30#
發(fā)表于 2025-3-26 20:27:23 | 只看該作者
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