Open AccessLocating Multiple Optima via Brain Storm Optimization Algorithms
Author(s) -
Shi Cheng,
Junfeng Chen,
Xiujuan Lei,
Yuhui Shi
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2811542
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Locating multiple optima/peaks in a single run and maintaining these found optima until the end of a run is the goal of multimodal optimization. Three variants of brain storm optimization (BSO) algorithms, which include original BSO algorithm, BSO in objective space algorithm with Gaussian random variable, and BSO in objective space algorithm with Cauchy random variable, were utilized to solve multimodal optimization problems in this paper. The experimental tests were conducted on eight benchmark problems and its applications in seven nonlinear equation system problems. The performance and effectiveness of various BSO algorithms on solving multimodal optimization problems were validated based on the experimental results. The conclusions could be made that the global search ability and solutions maintenance ability of an algorithm needs to be balanced simultaneously on solving multimodal optimization problems.
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