# Niching Global Optimisation: Systematic Literature Review
## 2 Niching Paradigms
### Parallel Niching Paradigms
#### 2.2.3 Restricted Tournament Selection (RTS)
* (108) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Pseudo multi-population differential evolution for multimodal optimization. In Proceedings of the 2014 10 th International Conference on Natural Computation (ICNC), Xiamen, China, 19-21 August 2014; pp. 457-462. * (109) [PERSON]; [PERSON]; [PERSON] Quantum-inspired evolutionary algorithm with linkage learning. In Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC), Beijing, China, 6-11 July 2014; pp. 2467-2474. * (110) [PERSON]; [PERSON]; [PERSON]; [PERSON] A niching cumulative genetic algorithm with evaluated probability for multimodal optimization. In Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation, Vancouver, BC, Canada, 12-16 July 2014; pp. 1073-1076. * (111) [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON] Firefly algorithm for finding optimal shapes of electromagnetic devices. _IEEE Trans. Magn._**2015**, _52_, 1-4. [CrossRef]
* (112) [PERSON]; [PERSON]; [PERSON]; [PERSON] An embedded architecture for real-time object detection in digital images based on niching particle swarm optimization. _J. -Real-Time Image Process._**2015**, _10_, 75-89. [CrossRef]
* (113) [PERSON]; [PERSON]; [PERSON]. Improved differential evolution algorithm based on chaotic theory and a novel hill-valley method for large-scale multimodal optimization problems. In Proceedings of the 2015 International Congress on Technology, Communication and Knowledge (ICTCK), Mashhad, Iran, 11-12 November 2015; pp. 268-275. * (114) [PERSON]; [PERSON] Niche Particle Swarm Optimization Combined with Chaotic Mutation Application in Image Enhancement. _WSEAS Trans. Signal Process._**2016**, _12_, 148-154. * (115) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Multimodal estimation of distribution algorithms. _IEEE Trans. Cybern._**2016**, _47_, 636-650. [CrossRef] [PubMed]
* (116) [PERSON]; [PERSON]; [PERSON] A blind source separation algorithm based on dynamic niching particle swarm optimization. In Proceedings of the MATEC Web of Conferences, Amsterdam, The Netherlands, 23-25 March 2016; EDP Sciences: Les Ulis, France, 2016; Volume 61, p. 03008. * (117) [PERSON]; [PERSON]; [PERSON] Design optimization of composite laminated tube based on improved niching evolutionary algorithm. _Math. Probl. Eng._**2017**, _2017_, 3141534. [CrossRef]
* (118) [PERSON]; [PERSON]; [PERSON]; [PERSON]. Improved Search Mechanisms for the Fish School Search Algorithm. In _Intelligent Systems Design and Applications, Proceedings of the 16 th International Conference on Intelligent Systems Design and Applications (ISDA 2016), Porto, Portugal, 16-18 December 2016_; Springer: Berlin/Heidelberg, Germany, 2017; pp. 362-371. * (119) [PERSON]; [PERSON] Effect of a push operator in genetic algorithms for multimodal optimization. In _Computational Intelligence, Communications, and Business Analytics, Proceedings of the First International Conference, CICBA 2017, Kolkata, India, 24-25 March 2017_; Revised Selected Papers, Part I; Springer: Berlin/Heidelberg, Germany, 2017; pp. 3-21. * (120) [PERSON]; [PERSON]; [PERSON] Learning multimodal parameters: A bare-bones niching differential evolution approach. _IEEE Trans. Neural Netw. Learn. Syst._**2017**, _29_, 2944-2959. [CrossRef]
* (121) [PERSON]; [PERSON]; [PERSON] Identifying multiple optima in aerodynamic design spaces. In Proceedings of the 2018 Multidisciplinary Analysis and Optimization Conference, Atlanta, GA, USA, 25-29 June 2018; p. 3422. * (122) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Local binary pattern-based adaptive differential evolution for multimodal optimization problems. _IEEE Trans. Cybern._**2019**, _50_, 3343-3357. [CrossRef] [PubMed]* (123) [PERSON]; [PERSON]; [PERSON] Fireworks algorithm for multimodal optimization using a distance-based exclusive strategy. In Proceedings of the 2019 IEEE Congress on Evolutionary Computation (CEC), Wellington, New Zealand, 10-13 June 2019; pp. 2215-2220.