Paper Info
Title
A Markov Network Based Factorized Distribution Algorithm for Optimization
Abstract
In this paper we propose a population based optimization method that uses the estimation of probability distributions. To represent an approximate factorization of the probability, the algorithm employs a junction graph constructed from an independence graph. We show that the algorithm is able to extend the representation capabilities of previous algorithms that use factorizations. A number of functions are used to evaluate the performance of our proposal. The results of the experiments show that the algorithm is able to optimize the functions, and it overperforms other evolutionary algorithms that use factorizations.
Year
DOI
Venue
2003
10.1007/978-3-540-39857-8_31
ESM 2003: 17TH EUROPEAN SIMULATION MULTICONFERENCE: FOUNDATIONS FOR SUCCESSFUL MODELLING & SIMULATION
Keywords
Field
DocType
genetic algorithms,EDA,FDA,evolutionary optimization,estimation of distributions
Factor graph,Population,Mathematical optimization,Markov process,Estimation of distribution algorithm,Evolutionary algorithm,Computer science,Markov chain,Algorithm,Probability distribution,Genetic algorithm
Conference
Volume
ISSN
Citations 
2837
0302-9743
14
PageRank 
References 
Authors
0.77
5
1
Name
Order
Citations
PageRank
Roberto Santana135719.04