Crow Search Algorithm for Continuous Optimization Tasks

被引：0
|
作者：
Kowalski, Piotr A. [1 ,2 ]
Franus, Krystian [1 ]
Lukasik, Szymon [1 ,2 ]
机构：
[1] AGH Univ Sci & Technol, Div Informat Technol & Syst Res, Fac Phys & Appl Comp Sci, Al Mickiewicza 30, PL-30059 Krakow, Poland
[2] Polish Acad Sci, Syst Res Inst, Ul Newelska 6, PL-01447 Warsaw, Poland
来源：
2019 6TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT 2019) | 2019年
关键词：
Artificial Intelligence; Computational Intelligence; Optimization; Metaheuristic; Swarm Intelligence; Crow Search Algorithm; SYMBIOTIC ORGANISMS SEARCH; KRILL HERD; FIREFLY ALGORITHM; SELECTION;
D O I：
10.1109/codit.2019.8820600
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The paper provides an insight into the novel metaheuristic of the Crow Search Algorithm (CSA) as used for continuous optimization tasks. The presented procedure is inspired by the social behaviour of crows. Based on established CEC 2017 benchmark tasks instances, the paper concentrates on performed experimental parameter studies and on a comparison with the existing Particle Swarm Optimization strategy. Building on the test experiences, sets of internal parameters have been formulated which constitute recommendations for other numerical calculations. Finally, some concluding remarks on possible algorithm extensions are given.
引用
收藏
页码：7 / 12
页数：6
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