返回
Interactive autodidactic school: A new metaheuristic optimization algorithm for solving mathematical and structural design optimization problems
DOI:10.1016/j.compstruc.2020.106268.png)
摘要
En 中文
A new efficient and robust metaheuristic algorithm called Interactive Autodidactic School (IAS) is proposed in this paper to solve numerical optimization and structural design optimization problems. IAS is a population-based algorithm on the basis of the interactions between students in an autodidactic school with the goal of increasing their knowledge through a combination of self-teaching/self-learning, interactive discussion, criticism, and the competition. IAS is tested in twenty mathematical optimization and seven structural optimization problems. Subsequently, its optimum solution is compared with other well-known optimization algorithms. The obtained results confirmed that the proposed IAS algorithm gives best optimal solution and has excellent performance compared with other optimization methods. (C) 2020 Elsevier Ltd. All rights reserved.
Keyword:
Metaheuristic optimization
Interactive autodidactic school
Mathematical optimization
Structural optimization
期刊
C
IF:
4.8
论文数:
6.2K
被引数:
1.7W
机构
引用论文
Kinematic and kinetic differences in the execution of vertical jumps between people with good and poor ankle joint dorsiflexion踝关节背屈良好和不良的人在执行垂直跳跃时的运动学和动力学差异
Optimization of water distribution network design using the Shuffled Frog Leaping Algorithm基于混合蛙跳算法的供水管网优化设计
A level-set based IGA foiniulation for topology optimization of flexoelectric materials基于水平集的IGA模型用于挠曲电材料的拓扑优化

