# Niching Global Optimisation: Systematic Literature Review
## 2 Niching Paradigms
### Parallel Niching Paradigms
#### 2.2.3 Restricted Tournament Selection (RTS)
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Authors** & **Year** & **Algorithm** & **Theoretical Ground** & **Type** \\ \hline
[73] & 2020 & CNMM-PSO &
\begin{tabular}{c} Speciation-based PSO which preselects elite-based fitness values, navigates particles based on closest neighbourhood and updates non-elites using differential evolution. \\ \end{tabular} & Speciation \\ \hline
[126] & 2020 & WSA-NEP &
\begin{tabular}{c} Whale swarm algorithm with niche identification and escape mechanism prevents convergence to local optima by dynamically adjusting niche boundaries. \\ \end{tabular} & Speciation \\ \hline
[10] & 2020 & WOA-NS &
\begin{tabular}{c} Enhances whale optimisation algorithm with niche and local search techniques to identify multiple optima in complex search spaces. \\ \end{tabular} & Speciation \\ \hline
[127] & 2020 & MOFOA &
\begin{tabular}{c} Integrates forest optimisation algorithm with niche strategies to enhance exploration and avoid premature convergence in multimodal functions. \\ \end{tabular} & Speciation \\ \hline
[74] & 2021 & SDLCSDE &
\begin{tabular}{c} Double layer speciation DE which forms on a first layer of independent niches based on elite particles and m nearest neighbours followed by later formation of global subpopulation from niche heads to discover eventually missed optima. \\ \end{tabular} & Speciation \\ \hline
[128] & 2021 & NGWO &
\begin{tabular}{c} Grey wolf optimiser integrates niching mechanisms to enhance the exploration and exploitation balance, locating multiple optima in multimodal problems. \\ \end{tabular} & Speciation \\ \hline
[129] & 2021 & SGPSA &
\begin{tabular}{c} Simple gravitational particle swarm algorithm employs gravitational attraction within a particle swarm to maintain multiple solutions in multimodal optimisation. \\ \end{tabular} & Speciation \\ \hline
[130] & 2021 & AOBSO &
\begin{tabular}{c} Attention-oriented brainstorm optimisation integrates attention mechanisms with brainstorm optimisation and improve performance in multimodal optimisation, enhancing both local and global search capabilities and maintaining diverse solutions to avoid premature convergence. \\ \end{tabular} & Speciation \\ \hline
[131] & 2021 & AMP &
\begin{tabular}{c} Adaptive multilevel prediction method for dynamic multimodal optimisation integrates prediction strategies with adaptive niching techniques to handle dynamic changes in multimodal optimisation problems, maintaining diverse solutions and improving convergence speed. \\ \end{tabular} & Speciation \\ \hline
[54] & 2021 & ANRFWA &
\begin{tabular}{c} Adaptive niche radius fireworks algorithm introduces the concept of dominating space of local optima, dynamically adjusting the niche radius to maintain solution diversity and prevent premature convergence in multimodal optimisation problems. \\ \end{tabular} & Speciation \\ \hline
[132] & 2022 & CNEA &
\begin{tabular}{c} Compact niching evolutionary algorithm leverages niching strategies within a compact genetic algorithm framework to maintain multiple solutions and improve the accuracy of matching knowledge graphs. \\ \end{tabular} & Speciation \\ \hline
[133] & 2022 & PRS-MO &
\begin{tabular}{c} Partition-based random search method divides the search space into partitions and employs random search within partitions to maintain multiple solutions and enhance exploration. \\ \end{tabular} & Speciation \\ \hline \hline \end{tabular}
\end{table} 
Table 5: _Cont._

#### 2.2.6 Clustering

Clustering-based parallel niching techniques generate multiple subpopulations by grouping which uses clustering analysis and distance features. Typically, clustering differs from speciation in that clustering chooses the centroid of every niche based on proximity, while speciation selects centroids using an elitist mechanism whereby the most prominent individuals form seeds around which other individuals orbit. Algorithm 7 provides a pseudo-code of the clustering niching paradigm.