Grasshopper Optimisation Algorithm: Theory and application

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• 作者：Shahrzad Saremi^a ; ^b ; Seyedali Mirjalili^a ; ^b ; ^{seyedali.mirjalili@griffithuni.edu.au} ; ; Andrew Lewis^a
• 关键词：Optimization ; Optimization techniques ; Heuristic algorithm ; Metaheuristics ; Constrained optimization ; Benchmark ; Algorithm
• 刊名：Advances in Engineering Software
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：105
• 期：Complete
• 页码：30-47
• 全文大小：3765 K
• 卷排序：105

文摘

The Grasshopper Optimisation Algorithm inspired by grasshopper swarms is proposed. The GOA algorithm is benchmarked on challenging test functions. The results on the unimodal functions show the superior exploitation of GOA. The exploration ability of GOA is confirmed by the results on multimodal and composite functions. The results on structural design problems confirm the performance of GOA in practice.