A review of particle swarm optimization. Part II: hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications
By Alec Banks, Jonathan Vincent, Chukwudi Anyakoha. Natural Computing, 2008
515 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics
View Paper: https://www.semanticscholar.org/paper/b0574087d5b0b4d4ed4819bdd590a1b7c2024802
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Xin-She Yang
- Yaochu Jin
- Ran Cheng
- Suash Deb
- M. N. Ab Wahab
- Samia Nefti-Meziani
- Adham Atyabi
- Shenkai Gu
In Computational Theory and Mathematics
- Yaochu Jin
- Ran Cheng
- Xin-She Yang
- Suash Deb
- Shenkai Gu
- M. N. Ab Wahab
- Samia Nefti-Meziani
- Adham Atyabi
Citations in the corpus
- Feature selection for high-dimensional classification using a competitive swarm optimizer (2016, background): “…solving complex combinatorial optimization problems, various metaheuristics have been proposed, such as genetic algorithms (GAs) (Han and Kim 2002), differential evolution (DE) (Price et al. 2006), and particle swarm optimization (PSO) (Banks et al. 2008), among many others (Bianchi et al. 2009).”
- Particle Swarm Optimization for Single Objective Continuous Space Problems: A Review (2017, unknown): “(2007) was published as a separate article (Banks et al., 2008) and it reviewed hybridization in PSO, combinatorial PSO, constrained optimization using PSO, and applications of PSO.”
- A Comprehensive Review of Swarm Optimization Algorithms (2015, background): “The second to fourth steps get repeated until the termination condition is satisfied [40, 46–48].”
- Bat algorithm for multi-objective optimisation (2011, background): “Despite these challenges, multiobjective optimization has many powerful algorithms with many successful applications (Abbass and Sarker, 2002; Banks et al., 2008; Deb, 2001, Farina et al., 2004; Konak et al., 2006; Rangaiah, 2008; Marler and Arora, 2004).”
- Multiobjective cuckoo search for design optimization (2013, background): “Despite these challenges, multiobjective optimization has many powerful algorithms with many successful applications [1,4,10, 15,22,39,31,40,26].”
- Multiobjective firefly algorithm for continuous optimization (2012, background): “Despite these challenges, multiobjective optimization has many powerful algorithms with many successful applications [6, 13, 14, 15, 43].”