3.8 Proceedings Paper

Brain Storm Optimization in Objective Space Algorithm for Multimodal Optimization Problems

Journal

ADVANCES IN SWARM INTELLIGENCE, ICSI 2016, PT I
Volume 9712, Issue -, Pages 469-478

Publisher

SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-319-41000-5_47

Keywords

Brain storm optimization; Brain storm optimization in objective space; Multimodal optimization; Swarm intelligence

Ask authors/readers for more resources

The aim of multimodal optimization is to locate multiple peaks/optima in a single run and to maintain these found optima until the end of a run. In this paper, brain storm optimization in objective space (BSO-OS) algorithm is utilized to solve multimodal optimization problems. Our goal is to measure the performance and effectiveness of BSO-OS algorithm. The experimental tests are conducted on eight benchmark functions. Based on the experimental results, the conclusions could be made that the BSO-OS algorithm performs good on solving multimodal optimization problems. To obtain good performances on multimodal optimization problems, an algorithm needs to balance its global search ability and solutions maintenance ability.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

3.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available