Result Details

Pareto Bayesian Optimization Algorithm for the Multiobjective 0/1 Knapsack Problem

SCHWARZ, J.; OČENÁŠEK, J. Pareto Bayesian Optimization Algorithm for the Multiobjective 0/1 Knapsack Problem. Proceedings of the 7th International Mendel Conference on Soft Computing. Brno: Faculty of Mechanical Engineering BUT, 2001. p. 131-136. ISBN: 80-214-1894-X.
Type
conference paper
Language
English
Authors
Schwarz Josef, doc. Ing., CSc.
Očenášek Jiří, Ing.
Abstract

: This paper deals with the utilizing of the Bayesian optimization algorithm (BOA) for the Pareto bi-criteria optimization of the 0/1 knapsack problem. The main attention is focused on the incorporation of the 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 mainly on the bi-criteria optimization because of the visualization simplicity but it can be extended to multiobjective optimization, too.

Keywords

Knapsack problem, multiobjective optimization, Pareto set, evolutionary algorithms, Bayesian optimization algorithm, niching techniques

URL
Published
2001
Pages
131–136
Proceedings
Proceedings of the 7th International Mendel Conference on Soft Computing
Conference
MENDEL 2001, 7th International Conference of Soft Computing. Evolutionary Computation, Genetic Programing, Fuzzy Logic, Rough Sets, Neural Networks, Fractals, Bayesian Methods.
ISBN
80-214-1894-X
Publisher
Faculty of Mechanical Engineering BUT
Place
Brno
BibTeX 
@inproceedings{BUT5430,
  author="Josef {Schwarz} and Jiří {Očenášek}",
  title="Pareto Bayesian Optimization Algorithm for the Multiobjective 0/1 Knapsack Problem",
  booktitle="Proceedings of the 7th International Mendel Conference on Soft Computing",
  year="2001",
  pages="131--136",
  publisher="Faculty of Mechanical Engineering BUT",
  address="Brno",
  isbn="80-214-1894-X",
  url="http://www.fit.vutbr.cz/~schwarz/PDFCLANKY/mend01.pdf"
}
Research groups
Supercomputing Technologies Research Group SC@FIT (RG SC@FIT)
Departments
Faculty of Information Technology (FIT)
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