Parameter Setting in Evolutionary Algorithms

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Lobo, Fernando G. (Επιμελητής έκδοσης), Lima, Cláudio F. (Επιμελητής έκδοσης), Michalewicz, Zbigniew (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007.
• Σειρά: Studies in Computational Intelligence, 54
• Θέματα: Engineering.; Artificial intelligence.; Applied mathematics.; Engineering mathematics.; Appl.Mathematics/Computational Methods of Engineering.; Artificial Intelligence (incl. Robotics).

One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operato...

Πίνακας περιεχομένων:

• Parameter Setting in EAs: a 30 Year Perspective
• Parameter Control in Evolutionary Algorithms
• Self-Adaptation in Evolutionary Algorithms
• Adaptive Strategies for Operator Allocation
• Sequential Parameter Optimization Applied to Self-Adaptation for Binary-Coded Evolutionary Algorithms
• Combining Meta-EAs and Racing for Difficult EA Parameter Tuning Tasks
• Genetic Programming: Parametric Analysis of Structure Altering Mutation Techniques
• Parameter Sweeps for Exploring Parameter Spaces of Genetic and Evolutionary Algorithms
• Adaptive Population Sizing Schemes in Genetic Algorithms
• Population Sizing to Go: Online Adaptation Using Noise and Substructural Measurements
• Parameter-less Hierarchical Bayesian Optimization Algorithm
• Evolutionary Multi-Objective Optimization Without Additional Parameters
• Parameter Setting in Parallel Genetic Algorithms
• Parameter Control in Practice
• Parameter Adaptation for GP Forecasting Applications.