Numerical Optimization of Computer Models

By A. Tripathy. 1982

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Citations in the corpus

A review of clustering techniques and developments (2017, background): “The famous evolutionary approaches [60] include evolution strategies (ES) [61], evolutionary programming (EP) [62], genetic algorithm (GA) [63, 64], particle swarm optimization (PSO) [65-66], ant colony optimization (ACO) [67] etc.”
Multiple trial vectors in differential evolution for engineering design (2007, methodology): “death penalty (Schwefel 1981 ); (ii) static penalty, i.”
An improved swarm optimized functional link artificial neural network (ISO-FLANN) for classification (2012, background): “The selfadaptive evolutionary strategy (ES) is suited for local optimization due to its high probability of generating small Gaussian and Cauchy perturbation (Rudolph, 1997; Schwefel, 1981).”
Data clustering: a review (1999, methodology): “The best-known evolutionary techniques are genetic algorithms (GAs) [Holland 1975; Goldberg 1989], evolution strategies (ESs) [Schwefel 1981], and evolutionary programming (EP) [Fogel et al.”
A survey on optimization metaheuristics (2013, background): “Schwefel [237] introduced two further versions of multimembered ES , i.”
Complex Adaptations and the Evolution of Evolvability (2005, background): “…1967, Scharloo, 1987), multivariate mutation selection balance (Wagner, 1989a), the evolution of pleiotropy (Altenberg, 1995a), the study of epistatic eeects (Gimelfarb, 1989, Wagner et al., 1994), and in evolutionary algorithms (for instance: Altenberg, 1994; Banzhaa, 1994; Schwefel, 1981 ).”