模拟退火
元启发式
计算机科学
稳健性(进化)
算法
人工免疫系统
工程设计过程
人工智能
数学优化
工程类
数学
机械工程
生物化学
基因
化学
作者
Betül Sultan Yıldız,Pranav Mehta,Sadiq M. Sait,Natee Panagant,Sumit Kumar,Ali Rıza Yıldız
出处
期刊:MP MATERIALPRUEFUNG - MP MATERIALS TESTING
[De Gruyter]
日期:2022-07-01
卷期号:64 (7): 1043-1050
被引量:1
摘要
Abstract Nature-inspired algorithms known as metaheuristics have been significantly adopted by large-scale organizations and the engineering research domain due their several advantages over the classical optimization techniques. In the present article, a novel hybrid metaheuristic algorithm (HAHA-SA) based on the artificial hummingbird algorithm (AHA) and simulated annealing problem is proposed to improve the performance of the AHA. To check the performance of the HAHA-SA, it was applied to solve three constrained engineering design problems. For comparative analysis, the results of all considered cases are compared to the well-known optimizers. The statistical results demonstrate the dominance of the HAHA-SA in solving complex multi-constrained design optimization problems efficiently. Overall study shows the robustness of the adopted algorithm and develops future opportunities to optimize critical engineering problems using the HAHA-SA.
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