Pareto-based multi-objective differential evolution

By Feng Xue, Arthur C. Sanderson, Robert J. Graves. The 2003 Congress on Evolutionary Computation, 2003. CEC '03., 2003

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An efficient multiobjective differential evolution algorithm for engineering design (2009, methodology): “Such as Pareto DE (PDE) (Abbass et al. 2001), Pareto DE Approach (Madavan 2002), Multiobjective DE ( Xue et al. 2003 ), DEMO (Robiy ca nd Filipiy c 2005), GDE3 (Kukkonen and Lampinen 2005), and � -MyDE (Santana-Quintero and Coello 2005), which uses the� -dominance (Deb et al. 2003) to get a good dis”
GDE3: the third evolution step of generalized differential evolution (2005, result): “Performance of GDE3 is demonstrated with a set of test problems and the results are compared with other methods.”
Grasshopper optimization algorithm for multi-objective optimization problems (2017, methodology): “Other popular algorithms are: Multi-Objective Particle Swarm Optimization (MOPSO) [27–29] Multi-objective Ant Colony Optimization [30], Multi-Objective Differential Evolution [31], Multi-objective Evolution Strategy [32].”
DEMO: Differential Evolution for Multiobjective Optimization (2005, methodology): “In [9] no diversity metric was calculated.”