Real-Coded Extended Compact Genetic Algorithm based on Mixtures of Models

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This document describes a real-coded extended compact genetic algorithm (RECGA) based on mixtures of models. RECGA uses probabilistic models like Bayesian optimization algorithms but with simpler models than typically used in BOAs. It applies an estimation of distribution algorithm approach using probabilistic models to generate new candidate solutions rather than using recombination and mutation operators as in traditional genetic algorithms. The RECGA method is presented as a way to take advantages of both extended compact genetic algorithms and Bayesian optimization algorithms while using less complex probabilistic models.

Technology Business

Real-Coded Extended Compact Genetic
Algorithm based on Mixtures of Models
Pier Luca Lanzi, Luigi Nichetti, Kumara Sastry,
Davide Voltini, and David E. Goldberg

Prof. Pier Luca Lanzi

Estimation of Distribution Algorithms

Probabilistic New
Population Selection Model Population

Extended Compact Genetic Algorithm

OBUPM-2008, July 12, 2008, Atlanta, GA

Real-Coded Extended Compact Genetic Algorithm based on Mixtures of Models

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