Singh, Narinder http://orcid.org/0000-0003-3805-0188
Kaur, Jaspreet
Funding for this research was provided by:
Na (Na)
Article History
Accepted: 22 April 2021
First Online: 19 May 2021
Declarations
:
: Dr. Narinder Singh and Mrs. Jaspreet Kaur declare that they have no conflict of interest.
: Harmony search approach was firstly developed by Z.W. Geem et al. Geem et al. (CitationRef removed), Geem (CitationRef removed). The combination search is a music-inspired optimization technique. It is inspired by the criticism that the aim of music is to search for a perfect state of harmony.On the other side, Seyedali Mirjalili Mirjalili (CitationRef removed) developed a new nature-inspired approach known as sine–cosine algorithm (SCA) for solving different types of application of separate fields. This approach establishes the solution of various basic random agents and enables them to exclude them from a mathematical model based on the trigonometric sine and cosine functions as the best possible outcomes. I have studied theoretical models developed by various researchers, viz. genetic algorithm (GA) Chung and Li (CitationRef removed), Cai et al. (CitationRef removed), particle swarm optimization (PSO) Kennedy and Eberhart (CitationRef removed), ant colony optimization (ACO) Soares et al. (CitationRef removed), differential evolution (DE) Kumar and Chandrasekar (CitationRef removed), Kumar and Chandrasekar (CitationRef removed), hybrid genetic algorithm (HGA) Slimani and Bouktir (CitationRef removed), fuzzy-based hybrid particle swarm optimization (fuzzy HPSO) Hsun et al. (CitationRef removed), harmony search algorithm Sinsupan et al. (CitationRef removed), robust optimization (RO) Ben-Tal et al. (CitationRef removed), artificial neural network (ANN) Chowdhury (CitationRef removed), biogeography-based optimization algorithm (BBO) Simon (CitationRef removed), gray wolf optimization (GWO) Mirjalili et al. (CitationRef removed), tabu search (TS) Abido (CitationRef removed), krill herd algorithm (KHA) Mukherjee and Mukherjee (CitationRef removed), ant lion optimizer (ALO) Mirjalili (CitationRef removed), gravitational search algorithm (GSA) Duman et al. (CitationRef removed), sine–cosine algorithm (SCA) Mirjalili (CitationRef removed), dragonfly algorithm (DA) Mirjalili (CitationRef removed), black hole-based optimization (BHBO) Bouchekara (CitationRef removed), whale optimization algorithm (WOA) Mirjalili (CitationRef removed), adaptive group search optimization (AGSO) Daryani et al. (CitationRef removed), multi-verse optimizer (MVO) Daryani et al. (CitationRef removed), moth flame optimizer (MFO) Mirjalili (CitationRef removed), cuckoo search (CS) Mirjalili (CitationRef removed), grasshopper optimization algorithm (GOA) Mirjalili (CitationRef removed), one half personal best position particle swarm optimization (OHGBPPSO) Singh and Singh (CitationRef removed), personal best position particle swarm optimization (PBPPSO) Singh and Singh (CitationRef removed), half mean particle swarm optimization algorithm (HMPSO) Singh et al. (CitationRef removed), HAGWO Singh and Hachimi (CitationRef removed), hybrid particle swarm optimization (HPSO) Singh et al. (CitationRef removed), HPSOGWO Singh and Singh (CitationRef removed), hybrid MGBPSO-GSA Singh and Singh (CitationRef removed), HGWOSCA Singh and Singh (CitationRef removed), MGWO Singh and Singh (CitationRef removed), MVGWO Singh (CitationRef removed), HSSAPSO Singh et al. (CitationRef removed), SChoA Kaur et al. (CitationRef removed), HSSASCA Singh et al. (CitationRef removed) and many more. Based on the work done by these authors, we have also proposed an hybrid approach, namely “hybrid sine–cosine algorithm–harmony search algorithm (HSCAHS)”. With this method, it is proposed to increase the convergence quality of the sine–cosine algorithm by accelerating the explore seeking instead of letting the approach running numerous iterations without any perfection. The new hybrid approach has been tested with numerous well-known standard test functions and some real-life applications. All experimental solutions ensured that the newer current access is a strong search approach for different compatibility applications. This article does not contain any studies with human participants or animals performed by any of the authors.
: No human/animal was involved in the current study. So informed consent is not applicable on my study.