Co-Operation of Biology Related Algorithms

被引：0

作者：

Akhmedova, Shakhnaz ^{[1
]}

Semenkin, Eugene ^{[1
]}

机构：

[1] Siberian State Aerosp Univ, Dept Syst Anal & Operat Res, Krasnoyarsk, Russia

来源：

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

关键词：

real-parameter black box optimization; nature-inspired strategy; swarm intelligence; cooperation; self-tuning;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

A new meta-heuristic algorithm, called Co-Operation of Biology Related Algorithms (COBRA), for solving real-parameter optimization problems is introduced and described. The algorithm is based on cooperation of biologically inspired algorithms such as Particle Swarm Optimization (PSO), Wolf Pack Search Algorithm (WPS), Firefly Algorithm (FFA), Cuckoo Search Algorithm (CSA) and Bat Algorithm (BA). The proposed algorithm performance is evaluated on given 28 test functions and its workability and usefulness is demonstrated. Ways of algorithm improvement are discussed.

引用

页码：2207 / 2214

页数：8

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