PMID- 35588436
OWN - NLM
STAT- MEDLINE
DCOM- 20220523
LR  - 20220716
IS  - 1932-6203 (Electronic)
IS  - 1932-6203 (Linking)
VI  - 17
IP  - 5
DP  - 2022
TI  - CSCAHHO: Chaotic hybridization algorithm of the Sine Cosine with Harris Hawk 
      optimization algorithms for solving global optimization problems.
PG  - e0263387
LID - 10.1371/journal.pone.0263387 [doi]
LID - e0263387
AB  - Because of the No Free Lunch (NFL) rule, we are still under the way developing 
      new algorithms and improving the capabilities of the existed algorithms. Under 
      consideration of the simple and steady convergence capability of the sine cosine 
      algorithm (SCA) and the fast convergence rate of the Harris Hawk optimization 
      (HHO) algorithms, we hereby propose a new hybridization algorithm of the SCA and 
      HHO algorithm in this paper, called the CSCAHHO algorithm henceforth. The energy 
      parameter is introduced to balance the exploration and exploitation procedure for 
      individuals in the new swarm, and chaos is introduced to improve the randomness. 
      Updating equations is redefined and combined of the equations in the SCA and HHO 
      algorithms. Simulation experiments on 27 benchmark functions and CEC 2014 
      competitive functions, together with 3 engineering problems are carried out. 
      Comparisons have been made with the original SCA, HHO, Archimedes optimization 
      algorithm (AOA), Seagull optimization algorithm (SOA), Sooty Tern optimization 
      algorithm (STOA), Arithmetic optimizer (AO) and Chimp optimization algorithm 
      (ChOA). Simulation experiments on either unimodal or multimodal, benchmark or 
      CEC2014 functions, or real engineering problems all verified the better 
      performance of the proposed CSAHHO, such as faster convergence rate, low residual 
      errors, and steadier capability. Matlab code of this algorithm is shared in Gitee 
      with the following address: https://gitee.com/yuj-zhang/cscahho.
FAU - Zhang, Yu-Jun
AU  - Zhang YJ
AUID- ORCID: 0000-0003-3016-8843
AD  - School of Electronics and Information Engineering, Jingchu University of 
      Technology, Jingmen, China.
FAU - Yan, Yu-Xin
AU  - Yan YX
AD  - Academy of Arts, Jingchu University of Technology, Jingmen, China.
FAU - Zhao, Juan
AU  - Zhao J
AUID- ORCID: 0000-0001-7047-2001
AD  - School of Electronics and Information Engineering, Jingchu University of 
      Technology, Jingmen, China.
FAU - Gao, Zheng-Ming
AU  - Gao ZM
AUID- ORCID: 0000-0003-1566-7134
AD  - School of Computer Engineering, Jingchu University of Technology, Jingmen, China.
AD  - Institute of Intelligent Information Technology, Hubei Jingmen Industrial 
      Technology Research Institute, Jingmen, China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20220519
PL  - United States
TA  - PLoS One
JT  - PloS one
JID - 101285081
SB  - IM
MH  - *Algorithms
MH  - Animals
MH  - Benchmarking
MH  - Birds
MH  - Computer Simulation
MH  - *Falconiformes
MH  - Humans
MH  - Problem Solving
PMC - PMC9119509
COIS- The authors have declared that no competing interests exist.
EDAT- 2022/05/20 06:00
MHDA- 2022/05/24 06:00
PMCR- 2022/05/19
CRDT- 2022/05/19 16:57
PHST- 2021/11/22 00:00 [received]
PHST- 2022/01/19 00:00 [accepted]
PHST- 2022/05/19 16:57 [entrez]
PHST- 2022/05/20 06:00 [pubmed]
PHST- 2022/05/24 06:00 [medline]
PHST- 2022/05/19 00:00 [pmc-release]
AID - PONE-D-21-36903 [pii]
AID - 10.1371/journal.pone.0263387 [doi]
PST - epublish
SO  - PLoS One. 2022 May 19;17(5):e0263387. doi: 10.1371/journal.pone.0263387. 
      eCollection 2022.