An Overview of Evolutionary Algorithms for Parameter Optimization

By Thomas Bäck, Hans-Paul Schwefel. 1993

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Citations in the corpus

Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks (2017, methodology): “As such, it differs from parameter optimization (B ¨ ack and Schwefel, 1993) in which search spaces are often static.”
Evolution of an artificial neural network based autonomous land vehicle controller (1996, methodology): “A comprehensive overview of evolutionary algorithms, and their applications to parameter optimization tasks, can be found in [ 3 ], [121.”
Evolutionary programming using mutations based on the Levy probability distribution (2004, background): “The parameters and are defined as [17] (27) Step 3) From parents and their offspring, calculate their fitness values .”
Multicriteria Optimization and Decision Making: Principles, Algorithms and Case Studies (2024, unknown): “Nowadays, the boundaries between these subfields became more fluid and the methods are often grouped together using the term Evolutionary Algorithms (see [3]).”
Evolutionary programming techniques for economic load dispatch (2003, methodology): “Experiments with self-adaptive EP have indicated efficient convergence to quality solutions [19], [ 23 ], [27], [28], [30].”
A survey on optimization metaheuristics (2013, background): “A number of review papers and text books exist with such details to which the reader is referred (see [11, 13, 25, 156]).”
Evolutionary computation: a unified approach (2018, methodology): “The ES community found that sexual reproduction with various forms of recombination improved the performance of their function optimizers (Bäck and Schwefel, 1993).”
Evolutionary and Computational Advantages of Neuromodulated Plasticity (2008, background): “For all other aspects of evolutionary search, refer to the extensive literature in the field (Goldberg, 1989; Bäck and Schwefel, 1993; Michalewicz, 1996).”
An improved swarm optimized functional link artificial neural network (ISO-FLANN) for classification (2012, methodology): “For this work we follow Bäck and Schwefel (1993) in setting the values of = 1/ √ 2n and = 1/ √ 2 √ n, respectively.”
A Cooperative Coevolutionary Approach to Function Optimization (1994, methodology): “The rst set of experiments is performed on four highly multimodal functions that have been used in other experimental comparisons of evolutionary algorithms [13, 6, 1].”