Journal articleSCHWARZ Josef and OČENÁŠEK Jiří. Multiobjective Bayesian Optimization Algorithm for Combinatorial Problems: Theory and Practice. NEURAL NETWORK WORLD. 2001, vol. 11, no. 5, pp. 423441. ISSN 12100552.  Publication language:  english 

Original title:  Multiobjective Bayesian Optimization Algorithm for Combinatorial Problems: Theory and Practice 

Title (cs):  Multiobjective Bayesian Optimization Algorithm for Combinatorial Problems: Theory and Practice 

Pages:  423441 

Place:  CZ 

Year:  2001 

Journal:  NEURAL NETWORK WORLD, Vol. 11, No. 5, CZ 

ISSN:  12100552 

URL:  http://www.fit.vutbr.cz/~schwarz/PDFCLANKY/nnw01.ps [PS] 

Keywords 

Multiobjective optimization, Pareto and non Pareto algorithms, evolutionary algorithms, probabilistic model, estimation distribution algorithms, Bayesian optimization algorithm, niching techniques 
Annotation 

This paper deals with the utilizing of the Bayesian optimization algorithm (BOA) for the multiobjective optimization of combinatorial problems. Three probabilistic models used in the Estimation Distribution Algorithms (EDA), such as UMDA, BMDA and BOA which allow to search effectively on the promising areas of the combinatorial search space are discussed. The main attention is focused on the incorporation of Pareto optimality concept into classical structure of the BOA algorithm. We have modified the standard algorithm BOA for one criterion optimization utilizing the known niching techniques to find the Pareto optimal set. The experiments are focused on tree classes of the combinatorial problems: artificial problem with known Pareto set, multiple 0/1 knapsack problem and the bisectioning of hypergraphs as well. 
BibTeX: 

@ARTICLE{
author = {Josef Schwarz and Ji{\v{r}}{\'{i}}
O{\v{c}}en{\'{a}}{\v{s}}ek},
title = {Multiobjective Bayesian Optimization Algorithm for
Combinatorial Problems: Theory and Practice},
pages = {423441},
journal = {NEURAL NETWORK WORLD},
volume = {11},
number = {5},
year = {2001},
ISSN = {12100552},
language = {english},
url = {http://www.fit.vutbr.cz/research/view_pub.php?id=6762}
} 
