Analysis of Bayesian Network Learning Techniques for a Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm: a case study on MNK Landscape
Author
Abstract
Suggested Citation
DOI: 10.1007/s10732-021-09469-x
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Aguirre, Hernan E. & Tanaka, Kiyoshi, 2007. "Working principles, behavior, and performance of MOEAs on MNK-landscapes," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1670-1690, September.
- Paulo S. G. de Mattos Neto & Manoel H. N. Marinho & Hugo Siqueira & Yara de Souza Tadano & Vivian Machado & Thiago Antonini Alves & João Fausto L. de Oliveira & Francisco Madeiro, 2020. "A Methodology to Increase the Accuracy of Particulate Matter Predictors Based on Time Decomposition," Sustainability, MDPI, vol. 12(18), pages 1-33, September.
- Shah, Ruchit & Reed, Patrick, 2011. "Comparative analysis of multiobjective evolutionary algorithms for random and correlated instances of multiobjective d-dimensional knapsack problems," European Journal of Operational Research, Elsevier, vol. 211(3), pages 466-479, June.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Madalina M. Drugan, 2019. "Random walk’s correlation function for multi-objective NK landscapes and quadratic assignment problem," Journal of Combinatorial Optimization, Springer, vol. 38(4), pages 1213-1262, November.
- Derbel, Bilel & Humeau, Jérémie & Liefooghe, Arnaud & Verel, Sébastien, 2014. "Distributed localized bi-objective search," European Journal of Operational Research, Elsevier, vol. 239(3), pages 731-743.
- Zhenghua Liu & Qijun Xiao & Rong Li, 2023. "Full Coverage Hourly PM 2.5 Concentrations’ Estimation Using Himawari-8 and MERRA-2 AODs in China," IJERPH, MDPI, vol. 20(2), pages 1-12, January.
- Mavrotas, George & Florios, Kostas, 2013. "An improved version of the augmented epsilon-constraint method (AUGMECON2) for finding the exact Pareto set in Multi-Objective Integer Programming problems," MPRA Paper 105034, University Library of Munich, Germany.
- Allmendinger, Richard & Handl, Julia & Knowles, Joshua, 2015. "Multiobjective optimization: When objectives exhibit non-uniform latencies," European Journal of Operational Research, Elsevier, vol. 243(2), pages 497-513.
- Alexandros Nikas & Angelos Fountoulakis & Aikaterini Forouli & Haris Doukas, 2022. "A robust augmented ε-constraint method (AUGMECON-R) for finding exact solutions of multi-objective linear programming problems," Operational Research, Springer, vol. 22(2), pages 1291-1332, April.
- Mădălina M. Drugan, 2018. "Scaling-up many-objective combinatorial optimization with Cartesian products of scalarization functions," Journal of Heuristics, Springer, vol. 24(2), pages 135-172, April.
- Marcella S. R. Martins & Myriam R. B. S. Delgado & Ricardo Lüders & Roberto Santana & Richard A. Gonçalves & Carolina P. Almeida, 2018. "Hybrid multi-objective Bayesian estimation of distribution algorithm: a comparative analysis for the multi-objective knapsack problem," Journal of Heuristics, Springer, vol. 24(1), pages 25-47, February.
- Mavrotas, George & Florios, Kostas & Figueira, José Rui, 2015. "An improved version of a core based algorithm for the multi-objective multi-dimensional knapsack problem: A computational study and comparison with meta-heuristics," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 25-43.
- Verel, Sébastien & Liefooghe, Arnaud & Jourdan, Laetitia & Dhaenens, Clarisse, 2013. "On the structure of multiobjective combinatorial search space: MNK-landscapes with correlated objectives," European Journal of Operational Research, Elsevier, vol. 227(2), pages 331-342.
- Probst, Malte & Rothlauf, Franz & Grahl, Jörn, 2017. "Scalability of using Restricted Boltzmann Machines for combinatorial optimization," European Journal of Operational Research, Elsevier, vol. 256(2), pages 368-383.
- Madjid Tavana & Kaveh Khalili-Damghani & Amir-Reza Abtahi, 2013. "A fuzzy multidimensional multiple-choice knapsack model for project portfolio selection using an evolutionary algorithm," Annals of Operations Research, Springer, vol. 206(1), pages 449-483, July.
- Ping Wang & Xuran He & Hongyinping Feng & Guisheng Zhang & Chenglu Rong, 2021. "A Hybrid Model for PM 2.5 Concentration Forecasting Based on Neighbor Structural Information, a Case in North China," Sustainability, MDPI, vol. 13(2), pages 1-19, January.
More about this item
Keywords
Many-objective optimization; Estimation of distribution algorithms; Structure learning techniques; Robustness;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:joheur:v:27:y:2021:i:4:d:10.1007_s10732-021-09469-x. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.