© 2015

Learning and Intelligent Optimization

9th International Conference, LION 9, Lille, France, January 12-15, 2015. Revised Selected Papers

  • Clarisse Dhaenens
  • Laetitia Jourdan
  • Marie-Eléonore Marmion
Conference proceedings LION 2015

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8994)

Also part of the Theoretical Computer Science and General Issues book sub series (LNTCS, volume 8994)

Table of contents

  1. Front Matter
    Pages I-XI
  2. M. Lindauer, H. Hoos, F. Hutter
    Pages 1-16
  3. Mustafa Mısır, Stephanus Daniel Handoko, Hoong Chuin Lau
    Pages 23-28
  4. Zhen-Zhen Li, Zhuo-Yao Zhong, Lian-Wen Jin
    Pages 29-42
  5. Mustafa Mısır, Stephanus Daniel Handoko, Hoong Chuin Lau
    Pages 59-73
  6. Willem Van Onsem, Bart Demoen, Patrick De Causmaecker
    Pages 74-88
  7. Martin Drozdik, Hernan Aguirre, Youhei Akimoto, Kiyoshi Tanaka
    Pages 89-103
  8. Shota Eguchi, Yuki Matsugano, Hirokazu Sakaguchi, Satoshi Ono, Hisato Fukuda, Ryo Furukawa et al.
    Pages 131-136
  9. Pierre Desport, Matthieu Basseur, Adrien Goëffon, Frédéric Lardeux, Frédéric Saubion
    Pages 137-150
  10. Marie-Eléonore Marmion, Olivier Regnier-Coudert
    Pages 151-164
  11. Matthieu Basseur, Adrien Goëffon, Hugo Traverson
    Pages 165-169
  12. Leticia Vargas, Nicolas Jozefowiez, Sandra Ulrich Ngueveu
    Pages 170-185
  13. Alan Tus, Andrea Rendl, Günther R. Raidl
    Pages 186-201
  14. Lars Kotthoff, Pascal Kerschke, Holger Hoos, Heike Trautmann
    Pages 202-217

About these proceedings


This book constitutes the thoroughly refereed post-conference proceedings of the 9th International Conference on Learning and Optimization, LION 9, which was held in Lille, France, in January 2015. The 31 contributions presented were carefully reviewed and selected for inclusion in this book. A large variety of topics are covered, such as benchmark problems and performance measures; tracking moving optima; dynamic multiobjective optimization; adaptation, learning, and anticipation; handling noisy fitness functions; using fitness approximations; searching for robust optimal solutions; comparative studies; hybrid approaches; theoretical analysis; and real-world applications.


Algorithm construction Answer set programming Bio-inspired approaches Bio-inspired optimization Classification Constraint solving Construction heuristics Data mining Decision tree Design Discrete optimization Experimentation Gaussian processes Machine learning approaches Metaheuristics Multi-criterion optimization and decision-making Optimization with randomized search heuristics Performance Real-world application Validation

Editors and affiliations

  • Clarisse Dhaenens
    • 1
  • Laetitia Jourdan
    • 2
  • Marie-Eléonore Marmion
    • 3
  1. 1.Lille UniversityVilleneuve d'AscqFrance
  2. 2.Lille UniversityVilleneuve d'AscqFrance
  3. 3.Lille UniversityVilleneuve d'AscqFrance

Bibliographic information