A constrained particle swarm optimization algorithm with Oracle penalty method

被引：2

作者：

Dong, Minggang ^{[1
]}

Cheng, Xiaohui ^{[1
]}

Niu, Qinzhou ^{[1
]}

机构：

[1] Guilin Univ Technol, Coll Informat Sci & Engn, Guilin 541004, Peoples R China

来源：

SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS, PTS 1-4 | 2013年 / 303-306卷

关键词：

particle swarm optimization; constrained optimization problems; Oracle penalty method; constraints handling;

D O I：

10.4028/www.scientific.net/AMM.303-306.1519

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

To solve constrained optimization problems, an Oracle penalty method-based comprehensive learning particle swarm optimization (OBCLPSO) algorithm was proposed. First, original Oracle penalty Was modified. Secondly, the modified Oracle penalty method was combine with comprehensive learning particle swarm optimization algorithm. Finally, experimental results and comparisons were given to demonstrate the optimization performances of OBCLPSO. The results show that the proposed algorithm is a very competitive approach for constrained optimization problems.

引用

页码：1519 / 1523

页数：5

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