A Bumble Bees Mating Optimization Algorithm for Global Unconstrained Optimization Problems

被引：0

作者：

Marinakis, Yannis ^{[1
]}

Marinaki, Magdalene ^{[2
]}

Matsatsinis, Nikolaos ^{[1
]}

机构：

[1] Tech Univ Crete, Dept Prod Engn & Management, Decis Support Syst Lab, Khania 73100, Crete, Greece

[2] Tech Univ Crete, Dept Prod Engn & Management, Ind Syst Control Lab, Khania 73100, Crete, Greece

来源：

NICSO 2010: NATURE INSPIRED COOPERATIVE STRATEGIES FOR OPTIMIZATION | 2010年 / 284卷

关键词：

HBMO ALGORITHM; SWARM;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A new nature inspired algorithm, that simulates the mating behavior of the bumble bees, the Bumble Bees Mating Optimization (BBMO) algorithm, is presented in this paper for solving global unconstrained optimization problems. The performance of the algorithm is compared with other popular metaheuristic and nature inspired methods when applied to the most classic global unconstrained optimization problems. The methods used for comparisons are Genetic Algorithms, Island Genetic Algorithms, Differential Evolution, Particle Swarm Optimization, and the Honey Bees Mating Optimization algorithm. A high performance of the proposed algorithm is achieved based on the results obtained.

引用

页码：305 / +

页数：4

共 27 条

[1]

Abbass HA, 2001, IEEE C EVOL COMPUTAT, P207, DOI 10.1109/CEC.2001.934391

[2] Honey-bee mating optimization (HBMO) algorithm for optimal reservoir operation [J].