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Titlebook: Engineering Applications of Modern Metaheuristics; Taymaz Akan,Ahmed M. Anter,Diego Oliva Book 2023 The Editor(s) (if applicable) and The

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樓主: 人工合成
41#
發(fā)表于 2025-3-28 18:08:24 | 只看該作者
42#
發(fā)表于 2025-3-28 21:37:02 | 只看該作者
Optimizing a Real Case Assembly Line Balancing Problem Using Various Techniques,ositional Weight (RPW), a modified version of RPW which is called Revised-RPW, and the Revised-COMSOAL, which is a recent-proposed, and one of the most efficient heuristic methods, are used to balance the production line and workstations, assuming deterministic tasks’ processing times.
43#
發(fā)表于 2025-3-29 00:36:57 | 只看該作者
Multi-circle Detection Using Multimodal Optimization,arm optimization (PSO) and local search is employed to locate all exciting circle in the image. The experiments on benchmark images show that our scheme can perform multi circle detection successfully.
44#
發(fā)表于 2025-3-29 06:50:19 | 只看該作者
H. Block,J. Ertelt,B. Nackunstz), salp swarm algorithm (SSA), and tree-seed algorithm (TSA)—are used for solving the minimum TPC optimization problem. The obtained results, convergence graphs, and standard deviations are showed that ABC is the best swarm intelligence algorithm, and the TSA is the most robust algorithm in this experimental environment.
45#
發(fā)表于 2025-3-29 09:58:23 | 只看該作者
46#
發(fā)表于 2025-3-29 11:52:55 | 只看該作者
47#
發(fā)表于 2025-3-29 19:37:48 | 只看該作者
48#
發(fā)表于 2025-3-29 20:08:15 | 只看該作者
A Meta-Heuristic Algorithm Based on the Happiness Model,m and some well-known algorithms will be 30 times applied on the benchmark functions and then compared with statistical value and Wilcoxon signed-rank test. As a consequence, the performance, reliability, and stability of our work have been demonstrated better than the others.
49#
發(fā)表于 2025-3-30 01:05:41 | 只看該作者
,Optimization of?Demand Response,ptimization techniques for solving the complex demand response problem is presented. It also discusses various factors that affect the demand response and its problem formulation. In the end a list of publications are enlisted which have used evolutionary optimization techniques to solve demand response.
50#
發(fā)表于 2025-3-30 08:01:24 | 只看該作者
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