ON STAGNATION OF THE DIFFERENTIAL EVOLUTION ALGORITHM

By Jouni Lampinen, I. Zelinka. 2000

340 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/dac431ea817da7833d2b6535455219ffa1af3108

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Citations in the corpus

Recent advances in differential evolution: a survey and experimental analysis (2010, methodology): “The former having been appreciative of and investigating the DE structure, see Storn (1996b), Storn and Price (1997), Tvrdík and Krivý (1999), and Lampinen and Zelinka (2000) while the latter applied this simple and powerful tool to the most various set of engineering problems, see e.g. Storn…”
A constraint handling approach for the differential evolution algorithm (2002, background): “Practical advice on how to select control parameters NP, F and CR can be found in [9, 12, 13], for example.”
Differential Evolution Using a Neighborhood-Based Mutation Operator (2009, background): “Practical experience, however, shows that DE may occasionally stop proceeding toward the global optimum even though the population has not converged to a local optimum or any other point [15].”
Differential Evolution: A Survey of the State-of-the-Art (2011, background): “Recently in works like [S31] and [S32], chaotic sequences are combined with DE in order to enhance its population diversity and thus to avoid the state of stagnation, when a standard DE may occasionally stop proceeding toward the global optimum virtually without any obvious reasons [41].”
Daily suspended sediment modelling using a fuzzy differential evolution approach / Modélisation journalière des matières en suspension par une approche d’évolution différentielle floue (2004, methodology): “Practical advice on how to select control parameters NP, F and CR can be found in Lampinen & Zelinka (2000), for example.”
Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization (2009, background): “Inappropriate choice of strategies and parameters may lead to premature convergence or stagnation , which have been extensively demonstrated in [8], [16], [17], [24], and [29].”
Differential evolution with multi-population based ensemble of mutation strategies (2016, background): “In other words, the inappropriate selection of strategies and parameters may lead to a premature convergence, stagnation, or a waste of computational resources [13,16,27,38,65].”
Spider Monkey Optimization algorithm for numerical optimization (2014, background): “Also some studies proved that DE sometimes stops proceeding toward the global optima even though the population has not converged to local optima or any other point [18].”
Seeker Optimization Algorithm for Optimal Reactive Power Dispatch (2009, background): “Several studies have shown that the DE is prone to not only premature convergence but also stagnation [22], [23], and that a successful location of the global optimum depends on choosing the correct”