Výsledky vyhledávání - "kriging-menetelmä"

Treed Gaussian Process Regression for Solving Offline Data-Driven Continuous Multiobjective Optimization Problems

Autor: Atanu Mazumdar, Manuel López-Ibáñez, Tinkle Chugh, Jussi Hakanen, Kaisa Miettinen

For offline data-driven multiobjective optimization problems (MOPs), no new data is available during the optimization process. Approximation models (or surrogates) are first built using the provided offline data and an optimizer, e.g. a multiobjectiv

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6b81c9a3e3b4e46da7eef06c74f626f9
http://urn.fi/URN:NBN:fi:jyu-202306133715

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Probabilistic Selection Approaches in Decomposition-based Evolutionary Algorithms for Offline Data-Driven Multiobjective Optimization

Autor: Atanu Mazumdar, Tinkle Chugh, Jussi Hakanen, Kaisa Miettinen

In offline data-driven multiobjective optimization, no new data is available during the optimization process. Approximation models, also known as surrogates, are built using the provided offline data. A multiobjective evolutionary algorithm can be ut

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5928d01c1c9616934d8fabf43296addb
http://urn.fi/URN:NBN:fi:jyu-202210054798

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Optimistic NAUTILUS navigator for multiobjective optimization with costly function evaluations

Autor: Bhupinder Singh Saini, Michael Emmerich, Atanu Mazumdar, Bekir Afsar, Babooshka Shavazipour, Kaisa Miettinen

We introduce novel concepts to solve multiobjective optimization problems involving (computationally) expensive function evaluations and propose a new interactive method called O-NAUTILUS. It combines ideas of trade-off free search and navigation (wh

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b2d45539ce8b59d153bfc2f6ee716b05
http://urn.fi/URN:NBN:fi:jyu-202201111077

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An Interactive Framework for Offline Data-Driven Multiobjective Optimization

Autor: Tinkle Chugh, Atanu Mazumdar, Jussi Hakanen, Kaisa Miettinen

Publikováno v: Lecture Notes in Computer Science ISBN: 9783030637095
BIOMA

We propose a framework for solving offline data-driven multiobjective optimization problems in an interactive manner. No new data becomes available when solving offline problems. We fit surrogate models to the data to enable optimization, which intro

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e69c0b59f13528212a423257ecbf5e9
http://urn.fi/URN:NBN:fi:jyu-202011266788

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