头脑风暴优化算法

讲座题目：头脑风暴优化算法

讲座人：史玉回  南方科技大学 计算机科学与工程系讲座教授，IEEE Fellow

讲座时间：10:30-12:00

讲座日期：2017年5月26日

地点：长安校区 文津楼三段4层必赢线路检测中心报告厅

主办单位：必赢线路检测中心  生物大数据计算研究团队

讲座内容：

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。BSO 算法通过聚类/分类方法分析解集合构成，基于解的分布生成新解，经过迭代求解，具有求解过程不依赖数学模型的特点。本报告将首先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，包括发展式群体智能、群体多样性、求解不同类型问题和实际应用的研究进展进行了全面的综述。最后对头脑风暴优化算法有待进一步研究的问题进行展望。

讲座人简介：

史玉回，南方科技大学计算机科学与工程系讲座教授，IEEE Fellow。主要从事脑风暴优化算法；粒子群优化算法；群体智能；演化计算；机器学习；计算智能；人工智能；数据科学；智能系统等方面的研究。在IEEE Trans.等期刊和会议上发表论文过百篇，论文引用46900余次。史玉回教授是粒子群优化算法创始人之一，也是头脑风暴优化算法创始人，担任International Journal of Swarm Intelligence Research 国际期刊主编，IEEE Transactions on Evolutionary Computation 副主编。参与组织过多个群体智能领域的顶级国际学术会议，在群体智能领域合著过两本英文专著。

Brain Storm Optimization Algorithms

Title of Lecture: Brain Storm Optimization Algorithms

Lecturer: Yuhui Shi, IEEE Fellow, Chair Professor, Department of Computer Science and Engineering, Southern University of Science and Technology

Time: 10:30-12:00

Date: 2017-5-26

Venue: Academic Hall, School of Computer Science, Chang’an Campus

Hosted by: School of Computer Science

About the Lecture:

For swarm intelligence algorithms, each individual in the swarm represents a solution in the search space, and it also can be seen as a data sample from the search space. Based on the analyses of these data, more effective algorithms and search strategies could be proposed. Brain storm optimization (BSO) algorithm is a new and promising swarm intelligence algorithm, which simulates the human brainstorming process. Through the convergent operation and divergent operation, individuals in BSO are grouped and diverged in the search space/objective space. In this Talk, the history development, and the state-of-the-art of the BSO algorithm are reviewed. Every individual in the BSO algorithm is not only a solution to the problem to be optimized, but also a data point to reveal the landscape of the problem. Swarm intelligence and data mining techniques can be combined to produce benefits above and beyond what either method could achieve alone.

Profile of the Lecturer:

Yuhui Shi received the Ph.D. degree in electronic engineering from Southeast University, Nanjing, China, in 1992. He was with Electronic Data Systems Corporation, Indianapolis, IN, USA. He is a Chair Professor with the Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China. His current research interests include computational intelligence techniques such as swarm intelligence and their applications.

Dr. Shi is the Editor-in-Chief of the International Journal of Swarm Intelligence Research.