Teaching and Learning best Differential Evoltuion with Self Adaptation for Real Parameter Optimization

被引：0

作者：

Biswas, Subhodip ^{[1
]}

Kundu, Souvik ^{[1
]}

Das, Swagatam ^{[2
]}

Vasilakos, Athanasios V. ^{[3
]}

机构：

[1] Jadavpur Univ, Dept Elect & Telecommun Engn, Kolkata 700132, W Bengal, India

[2] Indian Stat Inst, Elect & Commun Sci Unit, Kolkata 700108, India

[3] Kuwait Univ, Fac Sci, Dept Comp Sci, Kuwait, Kuwait

来源：

2013 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2013年

关键词：

differential evolution; optimization; real parameter; self-adaptation; teaching and learning; EVOLUTION;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Differential Evolution (DE), a rather new members of the evolutionary computing paradigm, has rose to widespread popularity in a short time interval owing to its simple design and robust performance in a wide variety of problems. Inspired from the effect of the teacher on the knowledge gained by the learners in a class, we propose a teaching and learning based self-adaptive DE (TLBSaDE) for solving real parameter optimization problems. A benchmark suite consisting of 28 test problems, proposed for the CEC 2013 Special Session and Competition on Real Parameter Optimization, is used. The results are obtained on 10, 30 and 50 dimensional problems.

引用

页码：1115 / 1122

页数：8

共 16 条

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