Learning and Intelligent Optimization

1. Front Matter

   Pages i-xv

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2. Interleaving Innovization with Evolutionary Multi-Objective Optimization in Production System Simulation for Faster Convergence

   • Amos H. C. Ng, Catarina Dudas, Henrik Boström, Kalyanmoy Deb

   Pages 1-18

3. Intelligent Optimization for the Minimum Labelling Spanning Tree Problem

   • Sergio Consoli, José Andrés Moreno Pérez, Nenad Mladenović

   Pages 19-23

4. A Constraint Satisfaction Approach to Tractable Theory Induction

   • John Ahlgren, Shiu Yin Yuen

   Pages 24-29

5. Features for Exploiting Black-Box Optimization Problem Structure

   • Tinus Abell, Yuri Malitsky, Kevin Tierney

   Pages 30-36

6. MOCA-I: Discovering Rules and Guiding Decision Maker in the Context of Partial Classification in Large and Imbalanced Datasets

   • Julie Jacques, Julien Taillard, David Delerue, Laetitia Jourdan, Clarisse Dhaenens

   Pages 37-51

7. Sharing Information in Parallel Search with Search Space Partitioning

   • Davide Lanti, Norbert Manthey

   Pages 52-58

8. Fast Computation of the Multi-Points Expected Improvement with Applications in Batch Selection

   • Clément Chevalier, David Ginsbourger

   Pages 59-69

9. R2-EMOA: Focused Multiobjective Search Using R2-Indicator-Based Selection

   • Heike Trautmann, Tobias Wagner, Dimo Brockhoff

   Pages 70-74

10. A Heuristic Algorithm for the Set Multicover Problem with Generalized Upper Bound Constraints

    • Shunji Umetani, Masanao Arakawa, Mutsunori Yagiura

    Pages 75-80

11. A Genetic Algorithm Approach for the Multidimensional Two-Way Number Partitioning Problem

    • P. C. Pop, O. Matei

    Pages 81-86

12. Adaptive Dynamic Load Balancing in Heterogeneous Multiple GPUs-CPUs Distributed Setting: Case Study of B&B Tree Search

    • Trong-Tuan Vu, Bilel Derbel, Nouredine Melab

    Pages 87-103

13. Multi-Objective Optimization for Relevant Sub-graph Extraction

    • Mohamed Elati, Cuong To, Rémy Nicolle

    Pages 104-109

14. PROGRESS: Progressive Reinforcement-Learning-Based Surrogate Selection

    • Stefan Hess, Tobias Wagner, Bernd Bischl

    Pages 110-124

15. Neutrality in the Graph Coloring Problem

    • Marie-Eléonore Marmion, Aymeric Blot, Laetitia Jourdan, Clarisse Dhaenens

    Pages 125-130

16. Kernel Multi Label Vector Optimization (kMLVO): A Unified Multi-Label Classification Formalism

    • Gilad Liberman, Tal Vider-Shalit, Yoram Louzoun

    Pages 131-137

17. Robust Benchmark Set Selection for Boolean Constraint Solvers

    • Holger H. Hoos, B. Kaufmann, T. Schaub, M. Schneider

    Pages 138-152

18. Boosting Sequential Solver Portfolios: Knowledge Sharing and Accuracy Prediction

    • Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann

    Pages 153-167

19. A Fast and Adaptive Local Search Algorithm for Multi-Objective Optimization

    • Duy Tin Truong

    Pages 168-173

20. An Analysis of Hall-of-Fame Strategies in Competitive Coevolutionary Algorithms for Self-Learning in RTS Games

    • Mariela Nogueira, Carlos Cotta, Antonio J. Fernández-Leiva

    Pages 174-188

This book constitutes the proceedings of the 7th International Conference on Learning and Optimization, LION 7, which was held in Catania, Italy, in January 2013. The 49 contributions presented in this volume were carefully reviewed and selected from 101 submissions. They explore the intersections and uncharted territories between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems.

• SAT solvers
• constraints
• game theory
• graph problems
• multi-objective optimization
• algorithm analysis and problem complexity

• Università Catania Dipto. Matematica e Informatica, Catania, Italy

  Giuseppe Nicosia

• Industrial & Systems Engineering, University of Florida, Gainesville, USA

  Panos Pardalos

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