Evaluating Performance of Honey Bee Mating Optimization

被引：4
|
作者：
Karimi, Somayeh [1 ]
Mostoufi, Navid [1 ]
Sotudeh-Gharebagh, Rahmat [1 ]
机构：
[1] Univ Tehran, Sch Chem Engn, Coll Engn, Proc Design & Simulat Res Ctr, Tehran, Iran
来源：
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS | 2014年 / 160卷 / 03期
基金：
美国国家科学基金会;
关键词：
Honey bees mating optimization; Swarm-based algorithms; Swarm intelligence;
D O I：
10.1007/s10957-013-0336-2
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
The honey bee mating optimization (HBMO) algorithm is presented and tested with various test functions, and its performance is compared with the genetic algorithm (GA). It is shown that the HBMO algorithm can overcome the weaknesses of the GA. The HBMO converges faster than the GA. Even when the HMBO starts from a more improper initial condition than the GA, it can reach a better solution in a smaller number of function evaluations. Furthermore, in some cases, the GA was not able to reach the global minimum.
引用
收藏
页码：1020 / 1026
页数：7
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