3 Migrating Forager Population in a Multi-population Artificial Bee Colony Algorithm with Modified Perturbation Schemes

被引:0
作者
Biswas, Subhodip [1 ]
Kundu, Souvik [1 ]
Bose, Digbalay [1 ]
Das, Swagatam [2 ]
Suganthan, P. N. [3 ]
Panigrahi, B. K. [4 ]
机构
[1] Jadavpur Univ, Dept Elect & Telecommun Engn, Kolkata 700032, India
[2] Indian Stat Inst, Elect & Commun Sci Unit, Kolkata 700108, West Bengal, India
[3] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
[4] Indian Inst Technol, Dept Elect Engn, New Delhi 110016, India
来源
2013 IEEE SYMPOSIUM ON SWARM INTELLIGENCE (SIS) | 2013年
关键词
Swarm Intelligence; Artificial Bee Colony; multi-population; strategy; migration; PARTICLE SWARM OPTIMIZER; DIFFERENTIAL EVOLUTION; PERFORMANCE;
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
Swarm Intelligent algorithms focus on imbibing the collective intelligence of a group of simple agents that can work together as a unit. This research article focus on a recently proposed swarm-based metaheuristic called the Artificial Bee Colony (ABC) algorithm and suggests modifications to the algorithmic framework in order to enhance its performance. The proposed ABC variant shall be referred to as MsABC_Fm (Multi swarm Artificial Bee Colony with Forager migration). MsABC_Fm maintains multiple swarm populations that apply different perturbation strategies and gradually migration of the population from worse performing strategy to the better mode of perturbation is promoted. To evaluate the performance of the algorithm, we conduct comparative study involving 8 algorithms and test the problems on 25 benchmark problems proposed in the Special Session on IEEE Congress on Evolutionary Competition 2005. The superiority of the MsABC_Fm approach is also highlighted statistically.
引用
收藏
页码:248 / 255
页数:8
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