[1]程适,陈俊风,孙奕菲,等.数据驱动的发展式头脑风暴优化算法综述[J].郑州大学学报(工学版),2018,39(03):22-28.
 Dwvelopmental Brain Storm Optimization Algorithms: From a Data-driven Perspective[J].Journal of Zhengzhou University (Engineering Science),2018,39(03):22-28.
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数据驱动的发展式头脑风暴优化算法综述()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
39
期数:
2018年03期
页码:
22-28
栏目:
出版日期:
2018-05-10

文章信息/Info

Title:
Dwvelopmental Brain Storm Optimization Algorithms: From a Data-driven Perspective
作者:
程适陈俊风孙奕菲史玉回
文献标志码:
A
摘要:
头脑风暴优化(Brain Storm Optimization,BSO)算法是一种新兴的群体智能优化方法,以众人集思广益解决问题为原型,抽取其中解决问题的模式,将其抽象为智能优化算法。介绍了头脑风暴优化算法的优化算子和基本原理,在对基本头脑风暴优化算法和目标空间中的头脑风暴优化算法比较的基础上,对头脑风暴优化算法的研究现状,包括群体多样性、求解不同类型问题和实际应用的研究现状进行了全面的综述。最后对头脑风暴优化算法有待进一步研究的问题进行了展望.
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.
更新日期/Last Update: 2018-05-03