Augmented Brain Storm Optimization with Mutation Strategies

Author(s):  
Xianghua Chu ◽  
Jiansheng Chen ◽  
Fulin Cai ◽  
Chen Chen ◽  
Ben Niu
2020 ◽  
Author(s):  
Pujari Jeevana Jyothi ◽  
Karteeka Pavan K ◽  
S M Raiyyan ◽  
T Rajasekhar

IET Software ◽  
2017 ◽  
Vol 11 (6) ◽  
pp. 292-300
Author(s):  
Osama Alkrarha ◽  
Jameleddine Hassine

2010 ◽  
Vol 97-101 ◽  
pp. 3714-3717 ◽  
Author(s):  
Wei Yan ◽  
Qi Gao ◽  
Zheng Gang Liu ◽  
Shan Hui Zhang ◽  
Yu Ping Hu

An improved multi-group self-adaptive evolutionary programming Algorithm is used to get adapt attribute weight for CBR system. Firstly, this paper analyses the adaptability function based on reference case base REF and testing case base TEST, develops a novel Bi-group self-adaptive evolutionary programming that overcome the lack of conventional evolutionary programming. In this Novel algorithm, evolution of Cauchy operator and Gauss operator are parallel performed with different mutation strategies, and the Gauss operator owns the ability of self-adaptation according to the variation of adaptability function. Information is exchanged when sub-groups are reorganized. Experiment results prove the validity of self-adaptive Algorithm and CBR design system is used successfully in engine design process.


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