# Niching Global Optimisation: Systematic Literature Review
## 2 Niching Paradigms
### Parallel Niching Paradigms
#### 2.2.3 Restricted Tournament Selection (RTS)
Also, several algorithms have relied on the use of function-evaluation-based radius-free approaches, such as the hill-valley concavity test [28]. In as much as this eliminates the need for radius estimation, several passes of the hill-valley test are more computationally intensive, especially for practical optimisation, whereby function evaluations are costly [29]. Other leading attempts have been made to estimate a single uniform niching radius, to adopt a variable niching radius, or rather to estimate the niching radius implicitly with statistical measures [5]. Tracking landscape topology and derivative information can be considered in future studies [222]. ### Local Exploitation Capacity and Resource Management

The number of search individuals in niche subpopulations is also a concerning parameter, especially in the proper exploitation of promising basins of convergence. Exploitation quality has been identified as a potential issue in parallel niching algorithms [12; 138; 223]. Further investigation of efficient local exploitation should be considered. The authors of [224] proposed a local search strategy in particle swarm optimisation which generates n additional similar particles around the pBest, thus forming a new exploitation niche. The authors of [151] proposed a local exploitation technique based on a Gaussian distribution to refine niche solutions and proposed a detection strategy of niche completion to save computational resources. Such techniques can be further investigated. ## 5 Conclusions

The current study comprehensively reviewed the theoretical paradigms of niching in global optimisation using data sourced from the Scopus database. Among the three main families of niching methods, parallel niching has received the most attention (73%) followed by hybrid methods (25%), with the family of hybrid-embedded methods being the most dominant one (17%). Speciation- and clustering-based parallel niching methods have been the most prominent algorithms in recent publications although not necessarily the best-performing techniques overall. In contrast, sequential niching has generated rather little interest since its inception, comprising only 2% of theoretical research efforts. However, this study still argues that the sequential niching paradigm is highly relevant for scalability in modern optimisation. The main challenge in the current state of the art lies in advancing the reliable performance of niching techniques in higher-dimensional spaces and assessing their scalability for problems with much larger numbers of peaks. The limited capacity of parallel niching methods to handle large search spaces indicates a need for more parallel algorithms with multiple restarts (parallel-sequential) to improve scalability. The favourable usage of parallel computing architectures may be beneficial. The need for computationally efficient adaptive niching radius techniques remains relevant, and the rigorous assessment of all major niching methods on scalable benchmarking test sets with diverse problem types is a worthy pursuit. Conceptualization, Y.M. and P.O. ; methodology, Y.M. and P.O. ; software, Y.M. ; validation, Y.M. and P.O. ; formal analysis, Y.M. ; investigation, Y.M. ; resources, Y.M., P.O., C.D. and E.v.W. ; data curation, Y.M. ; writing--original draft preparation, Y.M. ; writing--review and editing, Y.M. and P.O. ; visualization, Y.M. ; supervision, P.O. ; project administration, P.O., C.D. and E.v.W. ; funding acquisition, P.O., C.D. and E.v.W. All authors have read and agreed to the published version of the manuscript. ## Funding: This research received no external funding

**Data Availability Statement:** The current research data can be accessed in the SCOPUS database [[https://www.scopus.com/](https://www.scopus.com/)]([https://www.scopus.com/](https://www.scopus.com/)) upon inclusion of all inclusion and exclusion criteria in the PRISMA framework provided. ## Acknowledgments:

This research work was supported by the Tshwane University of Technology.