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Evolutionary Multi-Criterion Optimization

6th International Conference, EMO 2011, Ouro Preto, Brazil, April 5-8, 2011, Proceedings

  • Conference proceedings
  • © 2011

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Editors:
  1. Ricardo H. C. Takahashi

    1. Department of Mathematics, Federal University of Minas Gerais, Belo Horizonte, Brazil

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  2. Kalyanmoy Deb

    1. Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur, India

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  3. Elizabeth F. Wanner

    1. Department of Computer Engineering, Centro Federal de Educaçao Tecnológica de Minas Gerais, Belo Horizonte, Brazil

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  4. Salvatore Greco

    1. Faculty of Economics, University of Catania, Catania, Italy

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 6576)

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

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Conference proceedings info: EMO 2011.

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Table of contents (42 papers)

  1. Front Matter

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  2. Theoretical Issues

    1. Automated Innovization for Simultaneous Discovery of Multiple Rules in Bi-objective Problems

      • Sunith Bandaru, Kalyanmoy Deb
      Pages 1-15

    2. A Taxonomy of Online Stopping Criteria for Multi-Objective Evolutionary Algorithms

      • Tobias Wagner, Heike Trautmann, Luis Martí
      Pages 16-30

    3. Not All Parents Are Equal for MO-CMA-ES

      • Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
      Pages 31-45

    4. On Sequential Online Archiving of Objective Vectors

      • Manuel López-Ibáñez, Joshua Knowles, Marco Laumanns
      Pages 46-60

    5. On a Stochastic Differential Equation Approach for Multiobjective Optimization up to Pareto-Criticality

      • Ricardo H. C. Takahashi, Eduardo G. Carrano, Elizabeth F. Wanner
      Pages 61-75

    6. Pareto Cone ε-Dominance: Improving Convergence and Diversity in Multiobjective Evolutionary Algorithms

      • Lucas S. Batista, Felipe Campelo, Frederico G. Guimarães, Jaime A. Ramírez
      Pages 76-90

    7. Variable Preference Modeling Using Multi-Objective Evolutionary Algorithms

      • Christian Hirsch, Pradyumn Kumar Shukla, Hartmut Schmeck
      Pages 91-105

    8. On the Computation of the Empirical Attainment Function

      • Carlos M. Fonseca, Andreia P. Guerreiro, Manuel López-Ibáñez, Luís Paquete
      Pages 106-120

    9. Computing Hypervolume Contributions in Low Dimensions: Asymptotically Optimal Algorithm and Complexity Results

      • Michael T. M. Emmerich, Carlos M. Fonseca
      Pages 121-135

    10. Preference-Driven Co-evolutionary Algorithms Show Promise for Many-Objective Optimisation

      • Robin C. Purshouse, Cezar Jalbă, Peter J. Fleming
      Pages 136-150

    11. Adaptive Objective Space Partitioning Using Conflict Information for Many-Objective Optimization

      • Antonio López Jaimes, Carlos A. Coello Coello, Hernán Aguirre, Kiyoshi Tanaka
      Pages 151-165

    12. Effects of the Existence of Highly Correlated Objectives on the Behavior of MOEA/D

      • Hisao Ishibuchi, Yasuhiro Hitotsuyanagi, Hiroyuki Ohyanagi, Yusuke Nojima
      Pages 166-181

    13. Improved Random One-Bit Climbers with Adaptive ε-Ranking and Tabu Moves for Many-Objective Optimization

      • Joseph M. Pasia, Hernán Aguirre, Kiyoshi Tanaka
      Pages 182-196

    14. Framework for Many-Objective Test Problems with Both Simple and Complicated Pareto-Set Shapes

      • Dhish Kumar Saxena, Qingfu Zhang, João A. Duro, Ashutosh Tiwari
      Pages 197-211

  3. Algorithms

    1. A Preference Based Interactive Evolutionary Algorithm for Multi-objective Optimization: PIE

      • Karthik Sindhya, Ana Belen Ruiz, Kaisa Miettinen
      Pages 212-225

    2. Preference Ranking Schemes in Multi-Objective Evolutionary Algorithms

      • Marlon Alexander Braun, Pradyumn Kumar Shukla, Hartmut Schmeck
      Pages 226-240

    3. Interactive Multiobjective Mixed-Integer Optimization Using Dominance-Based Rough Set Approach

      • Salvatore Greco, Benedetto Matarazzo, Roman Słowiński
      Pages 241-253

    4. Very Large-Scale Neighborhood Search for Solving Multiobjective Combinatorial Optimization Problems

      • Thibaut Lust, Jacques Teghem, Daniel Tuyttens
      Pages 254-268

    5. Bilevel Multi-objective Optimization Problem Solving Using Progressively Interactive EMO

      • Ankur Sinha
      Pages 269-284
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  1. Evolutionary Multi-Criterion Optimization

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About this book

This book constitutes the refereed proceedings of the 6th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2011, held in Ouro Preto, Brazil, in April 2011. The 42 revised full papers presented were carefully reviewed and selected from 83 submissions. The papers deal with fundamental questions of EMO theory, such as the development of algorithmically efficient tools for the evaluation of solution-set quality , the theoretical questions related to solution archiving and others. They report on the continuing effort in the development of algorithms, either for dealing with particular classes of problems or for new forms of processing the problem information. Almost one third of the papers is related to EMO applications in a diversity of fields. Eleven papers are devoted to promote the interaction with the related field of Multi-Criterion Decision Making (MCDM).

Editors and Affiliations

  • Department of Mathematics, Federal University of Minas Gerais, Belo Horizonte, Brazil

    Ricardo H. C. Takahashi

  • Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur, India

    Kalyanmoy Deb

  • Department of Computer Engineering, Centro Federal de Educaçao Tecnológica de Minas Gerais, Belo Horizonte, Brazil

    Elizabeth F. Wanner

  • Faculty of Economics, University of Catania, Catania, Italy

    Salvatore Greco

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