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Learning and Intelligent Optimization

5th International Conference, LION 5, Rome, Italy, January 17-21, 2011, Selected Papers

  • Conference proceedings
  • © 2011

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Editors:
  1. Carlos A. Coello Coello

    1. Departmento de Computation, Centro de Investigacion y de Estudios, Avanzados del Instituto Politecnico Nacional (CINVESTAV-IPN), Mexico, Mexico

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 6683)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

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Conference proceedings info: LION 2011.

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About this book

This book constitutes the thoroughly refereed post-conference proceedings of the 5th International Conference on Learning and Intelligent Optimization, LION 5, held in Rome, Italy, in January 2011. The 32 revised regular and 3 revised short papers were carefully reviewed and selected from a total of 99 submissions. In addition to the contributions to the general track there are 11 full papers and 3 short papers presented at the following four special sessions; IMON: Intelligent Multiobjective OptimizatioN, LION-PP: Performance Prediction Self* EAs: Self-tuning, self-configuring and self-generating evolutionary algorithms LION-SWAP: Software and Applications.

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Table of contents (49 papers)

  1. Front Matter

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  2. Main Track (Regular Papers)

    1. Multivariate Statistical Tests for Comparing Classification Algorithms

      • Olcay Taner Yıldız, Özlem Aslan, Ethem Alpaydın
      Pages 1-15

    2. Using Hyperheuristics under a GP Framework for Financial Forecasting

      • Michael Kampouridis, Edward Tsang
      Pages 16-30

    3. On the Effect of Connectedness for Biobjective Multiple and Long Path Problems

      • Sébastien Verel, Arnaud Liefooghe, Jérémie Humeau, Laetitia Jourdan, Clarisse Dhaenens
      Pages 31-45

    4. Improving Parallel Local Search for SAT

      • Alejandro Arbelaez, Youssef Hamadi
      Pages 46-60

    5. Variable Neighborhood Search for the Time-Dependent Vehicle Routing Problem with Soft Time Windows

      • Stefanie Kritzinger, Fabien Tricoire, Karl F. Doerner, Richard F. Hartl
      Pages 61-75

    6. Solving the Two-Dimensional Bin Packing Problem with a Probabilistic Multi-start Heuristic

      • Lukas Baumgartner, Verena Schmid, Christian Blum
      Pages 76-90

    7. Genetic Diversity and Effective Crossover in Evolutionary Many-objective Optimization

      • Hiroyuki Sato, Hernán E. Aguirre, Kiyoshi Tanaka
      Pages 91-105

    8. An Optimal Stopping Strategy for Online Calibration in Local Search

      • Gianluca Bontempi
      Pages 106-115

    9. Analyzing the Effect of Objective Correlation on the Efficient Set of MNK-Landscapes

      • Sébastien Verel, Arnaud Liefooghe, Laetitia Jourdan, Clarisse Dhaenens
      Pages 116-130

    10. Instance-Based Parameter Tuning via Search Trajectory Similarity Clustering

      • Lindawati, Hoong Chuin Lau, David Lo
      Pages 131-145

    11. Effective Probabilistic Stopping Rules for Randomized Metaheuristics: GRASP Implementations

      • Celso C. Ribeiro, Isabel Rosseti, Reinaldo C. Souza
      Pages 146-160

    12. A Classifier-Assisted Framework for Expensive Optimization Problems: A Knowledge-Mining Approach

      • Yoel Tenne, Kazuhiro Izui, Shinji Nishiwaki
      Pages 161-175

    13. Robust Gaussian Process-Based Global Optimization Using a Fully Bayesian Expected Improvement Criterion

      • Romain Benassi, Julien Bect, Emmanuel Vazquez
      Pages 176-190

    14. Hierarchical Hidden Conditional Random Fields for Information Extraction

      • Satoshi Kaneko, Akira Hayashi, Nobuo Suematsu, Kazunori Iwata
      Pages 191-202

    15. Solving Extremely Difficult MINLP Problems Using Adaptive Resolution Micro-GA with Tabu Search

      • Asim Munawar, Mohamed Wahib, Masaharu Munetomo, Kiyoshi Akama
      Pages 203-217

    16. Adaptive Abnormality Detection on ECG Signal by Utilizing FLAC Features

      • Jiaxing Ye, Takumi Kobayashi, Tetsuya Higuchi, Nobuyuki Otsu
      Pages 218-225

    17. Gravitational Interactions Optimization

      • Juan J. Flores, Rodrigo López, Julio Barrera
      Pages 226-237

    18. On the Neutrality of Flowshop Scheduling Fitness Landscapes

      • Marie-Eléonore Marmion, Clarisse Dhaenens, Laetitia Jourdan, Arnaud Liefooghe, Sébastien Verel
      Pages 238-252

    19. A Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem

      • Yailen Martínez, Ann Nowé, Juliett Suárez, Rafael Bello
      Pages 253-262
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Other volumes

  1. Learning and Intelligent Optimization

Editors and Affiliations

  • Departmento de Computation, Centro de Investigacion y de Estudios, Avanzados del Instituto Politecnico Nacional (CINVESTAV-IPN), Mexico, Mexico

    Carlos A. Coello Coello

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