Optimal design of steel skeletal structures using the enhanced genetic algorithm methodology
钢的最佳的设计用提高的基因算法方法论的骨胳的结构作者机构：Department of Civil Engineering Osmaniye Korkut Ata University Osmaniye 80000 Turkey
出 版 物：《Frontiers of Structural and Civil Engineering》 (结构与土木工程前沿（英文版）)
年 卷 期：2019年第13卷第4期
页 面：863-889页
核心收录：
学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 08[工学]
基 金：Author thanks to both Prof. Dr. Hasancebi O.-METU Ankara Turkey for providing additional information about the design examples with 444 and 942-bar and reviewers for their contributions in the improvement of this article
主 题：design optimization genetic algorithm multiple populations neural network
摘 要：This study concerns with the design optimization of steel skeletal structures thereby utilizing both a real-life specification provisions and ready steel profiles named hot-rolled I sections. For this purpose, the enhanced genetic algorithm methodology named EGAwMP is utilized as an optimization tool. The evolutionary search mechanism of EGAwMP is constituted on the basis of generational genetic algorithm (GGA). The exploration capacity of EGAwMP is improved in a way of dividing an entire population into sub-populations and using of a radial basis neural network for dynamically adjustment of EGAwMP’s genetic operator parameters. In order to improve the exploitation capability of EGAwMP, the proposed neural network implementation is also utilized for prediction of more accurate design variables associating with a new design strategy, design codes of which are based on the provisions of LRFD_AISC V3 specification. EGAwMP is applied to determine the real-life ready steel profiles for the optimal design of skeletal structures with 105, 200, 444, and 942 members. EGAwMP accomplishes to increase the quality degrees of optimum designations Furthermore, the importance of using the real-life steel profiles and design codes is also demonstrated. Consequently, EGAwMP is suggested as a design optimization tool for the real-life steel skeletal structures.
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