Sayat Ibrayev1, Batyrkhan Omarov1,2,3,*, Arman Ibrayeva1, Zeinel Momynkulov1,2
CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 229-249, 2024, DOI:10.32604/cmc.2024.053075
- 15 October 2024
Abstract This research paper presents a comprehensive investigation into the effectiveness of the DeepSurNet-NSGA II (Deep Surrogate Model-Assisted Non-dominated Sorting Genetic Algorithm II) for solving complex multi-objective optimization problems, with a particular focus on robotic leg-linkage design. The study introduces an innovative approach that integrates deep learning-based surrogate models with the robust Non-dominated Sorting Genetic Algorithm II, aiming to enhance the efficiency and precision of the optimization process. Through a series of empirical experiments and algorithmic analyses, the paper demonstrates a high degree of correlation between solutions generated by the DeepSurNet-NSGA II and those obtained from… More >
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