Learning and intelligent optimization for material design innovation

Amir Mosavi, Timon Rabczuk

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

Abstract

Learning and intelligent optimization (LION) techniques enable problem-specific solvers with vast potential applications in industry and business. This paper explores such potentials for material design innovation and presents a review of the state of the art and a proposal of a method to use LION in this context. The research on material design innovation is crucial for the long-lasting success of any technological sector and industry and it is a rapidly evolving field of challenges and opportunities aiming at development and application of multi-scale methods to simulate, predict and select innovative materials with high accuracy. The LION way is proposed as an adaptive solver toolbox for the virtual optimal design and simulation of innovative materials to model the fundamental properties and behavior of a wide range of multi-scale materials design problems.

Original languageEnglish
Title of host publicationLearning and Intelligent Optimization - 11th International Conference, LION 11, Revised Selected Papers
PublisherSpringer Verlag
Pages358-363
Number of pages6
Volume10556 LNCS
ISBN (Print)9783319694030
DOIs
Publication statusPublished - 2017 Jan 1
Externally publishedYes
Event11th International Conference on Learning and Intelligent Optimization, LION 2017 - Nizhny Novgorod, Russian Federation
Duration: 2017 Jun 192017 Jun 21

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10556 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th International Conference on Learning and Intelligent Optimization, LION 2017
CountryRussian Federation
CityNizhny Novgorod
Period17/6/1917/6/21

Keywords

  • Machine learning
  • Material design
  • Optimization

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Mosavi, A., & Rabczuk, T. (2017). Learning and intelligent optimization for material design innovation. In Learning and Intelligent Optimization - 11th International Conference, LION 11, Revised Selected Papers (Vol. 10556 LNCS, pp. 358-363). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10556 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-69404-7_31