A hybrid simplex search and particle swarm optimization for unconstrained optimization

By Shu-Kai S. Fan, Erwie Zahara. European Journal of Operational Research, 2007

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Hybrid Nelder-Mead simplex search and particle swarm optimization for constrained engineering design problems (2009, methodology): “For further details of the hybrid NM–PSO for unconstrained optimization problem, see Fan and Zahara (2007).”
Derivative-free optimization: a review of algorithms and comparison of software implementations (2012, methodology): “Particle swarm optimization has enjoyed recent interest resulting in hybrid algorithms that combine the global scope of the particle swarm search with the faster local convergence of the Nelder–Mead simplex algorithm [46] or GSS methods [138].”
Frankenstein's PSO: A Composite Particle Swarm Optimization Algorithm (2009, positive): “These algorithmic components range from added constants in the particles’ velocityupdate rule [5] to stand-alone algorithms that are used as components of hybrid PSO algorithms [6].”
Teaching-Learning-Based Optimization: An optimization method for continuous non-linear large scale problems (2012, methodology): “96E 12 100 1857 0 Table 4 Details of benchmark functions considered by Shu and Erwie [24].”