Study of Parameter Sensitivity on Bat Algorithm

被引：3

作者：

Carvalho, Iago Augusto ^{[1
]}

da Rocha, Daniel G. ^{[2
]}

Rocha Silva, Joao Gabriel ^{[3
]}

Vieira, Vinicus da Fonseca ^{[2
]}

Xavier, Carolina Ribeiro ^{[2
]}

机构：

[1] Univ Fed Minas Gerais, Dept Comp Sci, Belo Horizonte, MG, Brazil

[2] Univ Fed Sao Joao Rei, Dept Comp Sci, Sao Joao Del Rei, Brazil

[3] Univ Fed Juiz Fora, Postgrad Program Computat Modeling, Juiz De Fora, Brazil

来源：

COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2017, PT I | 2017年 / 10404卷

关键词：

Bat algorithm; Sensitivity; Parameter analysis; Nonlinear optimization; Unconstrained optimization; OPTIMIZATION;

D O I：

10.1007/978-3-319-62392-4_36

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Heuristics and metaheuristics are known to be sensitive to input parameters. Bat algorithm (BA), a recent optimization metaheuristic, has a great number of input parameters that need to be adjusted in order to increase the quality of the results. Despites the crescent number of works with BA in literature, to the best of our knowledge, there is no work that aims the fine tuning of the parameters. In this work we use benchmark functions and more than 9 millions tests with BA in order to find the best set of parameters. Our experiments shown that we can have almost 14000% of difference in objective function value between the best and the worst set of parameters. Finally, this work shows how to choose input parameters in order to make Bat Algorithm to achieve better results.

引用

页码：494 / 508

页数：15

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