Cultured Artificial Fish Swarm Algorithm: An Experimental Evaluation

被引：0

作者：

Imam, Maryam Lami ^{[1
]}

Adebiyi, Busayo H. ^{[2
]}

Bello-Salau, Habeeb ^{[2
]}

Olarinoye, Gbenga A. ^{[3
]}

Momoh, Muyideen O. ^{[2
]}

机构：

[1] Univ Jos, Dept Elect & Elect Engn, Jos, Nigeria

[2] Ahmadu Bello Univ, Dept Comp Engn, Zaria, Nigeria

[3] Ahmadu Bello Univ, Dept Elect Engn, Zaria, Nigeria

来源：

2019 2ND INTERNATIONAL CONFERENCE OF THE IEEE NIGERIA COMPUTER CHAPTER (NIGERIACOMPUTCONF) | 2019年

关键词：

Artificial Fish Swarm Algorithm; Inertia Weight; Culture Algorithm; Test Functions; OPTIMIZATION;

D O I：

10.1109/nigeriacomputconf45974.2019.8949657

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this work, a Weighted Cultural Artificial Fish Swarm Algorithm (wCAFSA) which is an amendment of standard artificial fish swarm algorithm (AFSA) is proposed. This algorithm can adaptively select its parameters at every generation in order to reduce the ease at which standard AFSA falls into local optimal We first introduce inertial weight to adaptively determine visual distance and step size of AFSA thereafter, the Situational and Normative knowledge inherent in cultural algorithm are used to develop new variants of weighted cultural AFSA (wCAFSA Ns, wCAFSA sd, wCAFSA Ns+Sd and wCAFSA Ns+Nd). A collection of sixteen (16) optimization benchmark functions are used to test the performance of the algorithms. The simulation results disclosed that all the new variants of the wCAFSA outclassed the AFSA.

引用

页码：198 / +

页数：7

共 20 条

[1]

Adebiyi B. H., 2018, ARIDE ZONE J ENG TEC, V14, P491

[2]

[Anonymous], 2015, J ENG RES

[3] CADE: A hybridization of Cultural Algorithm and Differential Evolution for numerical optimization [J].