布谷鸟搜索
桁架
计算机科学
布谷鸟
数学优化
优化算法
算法
数学
工程类
结构工程
粒子群优化
动物
生物
作者
Nam Vo,Huy Tang,Jaehong Lee
标识
DOI:10.1016/j.asoc.2024.111435
摘要
A novel hybrid algorithm called Multi-Objective Hybrid Grey Wolf Cuckoo Search (MOGWOCS) is developed for spatial truss designs in this study. A new simple yet efficient mechanism to select the best candidates is proposed. Furthermore, harmonic averaging is employed to be a replacement for conventional arithmetic mean for higher effectiveness. Additionally, the Lévy flight in Cuckoo Search (CS) is utilized to increase efficiency in early searching and also reduce local entrapment possibility. For verification purposes, MOGWOCS is first performed on some mathematical functions and 11 CEC2020 mechanical problems. It is then examined on four large-scale truss design problems, in two of which multi-objective optimization is studied for the first time. To demonstrate the superiority of the proposed approach, five up-to-date algorithms, and various indicators are included for validation. It is found that MOGWOCS is able to produce solutions with higher optimality in terms of diversity and accuracy.
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