Beetle Antennae Search without Parameter Tuning (BAS-WPT) for Multi-objective Optimization

被引：25
作者：
Jiang, Xiangyuan [1 ,2 ]
Li, Shuai [2 ]
机构：
[1] Shandong Univ, Inst Marine Sci & Technol, Qingdao, Peoples R China
[2] Hong Kong Polytech Univ, Dept Comp, Hung Hom, Kowloon, Hong Kong, Peoples R China
来源：
FILOMAT | 2020年 / 34卷 / 15期
关键词：
Optimization; constraint; beetle antennae search; parameter tuning; ENGINEERING OPTIMIZATION; EVOLUTIONARY; ALGORITHM; INTEGER;
D O I：
10.2298/FIL2015113J
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Beetle antennae search (BAS) is an efficient meta-heuristic algorithm inspired by foraging behaviors of beetles. This algorithm includes several parameters for tuning and the existing results are limited to solve single objective optimization. This work pushes forward the research on BAS by providing one variant that releases the tuning parameters and is able to handle multi-objective optimization. This new approach applies normalization to simplify the original algorithm and uses a penalty function to exploit infeasible solutions with low constraint violation to solve the constraint optimization problem. Extensive experimental studies are carried out and the results reveal efficacy of the proposed approach to constraint handling.
引用
收藏
页码：5113 / 5119
页数：7
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