Dwvelopmental Brain Storm Optimization Algorithms: From a Data-driven Perspective
[1]Cheng Shi,Chen Junfeng,Sun Yifei,et al.Dwvelopmental Brain Storm Optimization Algorithms: From a Data-driven Perspective[J].Journal of Zhengzhou University (Engineering Science),2018,39(03):22-28.[doi:10.13705/j.issn.1671-6833.2018.03.003]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
39
Number of periods:
2018 03
Page number:
22-28
Column:
Public date:
2018-05-10
- Title:
- Dwvelopmental Brain Storm Optimization Algorithms: From a Data-driven Perspective
- Keywords:
- brain storm optimization; developmental swarm intelligence; convergent operation; divergent operation
- CLC:
- -
- Abstract:
- For swarm intelligence algorithms, each individual in the swarm represented a solution in the search space, and it also could be seen as a data sample from the search space. Brain storm optimization (BSO) algorithm was a new and promising swarm intelligence algorithm, which simulated the human brainstorming process. Through the convergent operation and divergent operation, individuals in BSO were grouped and diverged in the search space/objective space. In this paper, the development history, and the state-of-the-art of the BSO algorithm were reviewed. Every individual in the BSO algorithm was not only a solution to the problem to be optimized, but also a data point to reveal the landscape of the problem. Based on the survey of brain storm optimization algorithms, more analyses could be conducted to understand the function of BSO algorithm and more variants of BSO algorithms could be proposed t22o solve different problems.
- References:
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Last Update:
2018-05-03