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Data-Driven Interactive Multiobjective Optimization Using a Cluster-Based Surrogate in a Discrete Decision Space

Abstract
In this paper, a clustering based surrogate is proposed to be used in offline data-driven multiobjective optimization to reduce the size of the optimization problem in the decision space. The surrogate is combined with an interactive multiobjective optimization approach and it is applied to forest management planning with promising results.
Main Authors
Hakanen, Jussi Malmberg, Jose Ojalehto, Vesa Eyvindson, Kyle Nicosia, Giuseppe Pardalos, Panos Giuffrida, Giovanni Umeton, Renato Sciacca, Vincenzo
Format
Conferences Conference paper
Published
2019
Series
Lecture Notes in Computer Science
Subjects
data-driven optimization
surrogates
clustering
preference information
decision maker
boreal forest management
boreaalinen vyöhyke
klusterit
päätöksenteko
optimointi
metsänhoito
Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/28967579
Publisher
Springer
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-201911214960Käytä tätä linkitykseen.
Parent publication ISBN
978-3-030-13708-3
Review status
Peer reviewed
ISSN
0302-9743
DOI
https://doi.org/10.1007/978-3-030-13709-0_9
Conference
International Conference on Machine Learning, Optimization, and Data Science
Language
English
Published in
Lecture Notes in Computer Science
Is part of publication
LOD 2018 : Machine Learning, Optimization, and Data Science. 4th International Conference, LOD 2018, Volterra, Italy, September 13-16, 2018, Revised Selected Papers
Citation
  • Hakanen, J., Malmberg, J., Ojalehto, V., & Eyvindson, K. (2019). Data-Driven Interactive Multiobjective Optimization Using a Cluster-Based Surrogate in a Discrete Decision Space. In G. Nicosia, P. Pardalos, G. Giuffrida, R. Umeton, & V. Sciacca (Eds.), LOD 2018 : Machine Learning, Optimization, and Data Science. 4th International Conference, LOD 2018, Volterra, Italy, September 13-16, 2018, Revised Selected Papers (pp. 104-115). Springer. Lecture Notes in Computer Science, 11331. https://doi.org/10.1007/978-3-030-13709-0_9
License
In CopyrightOpen Access
Funder(s)
Research Council of Finland
Research Council of Finland
Funding program(s)
Akatemiahanke, SA
Profilointi, SA
Academy Project, AoF
Research profiles, AoF
Research Council of Finland
Additional information about funding
This research was supported by the Academy of Finland (projects no. 311877 and 287496) and is related to the thematic research area DEMO of the University of Jyväskylä.
Copyright© Springer Nature Switzerland AG 2019

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