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Evolutionary Multi-Criterion Optimization

9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings

  • Conference proceedings
  • © 2017

Overview

Editors:
  1. Heike Trautmann

    1. University of Münster, Münster, Germany

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  2. Günter Rudolph

    1. TU Dortmund University, Dortmund, Germany

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  3. Kathrin Klamroth

    1. University of Wuppertal, Wuppertal, Germany

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  4. Oliver Schütze

    1. CINVESTAV-IPN, Mexico City, Mexico

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  5. Margaret Wiecek

    1. Clemson University, Clemson, USA

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  6. Yaochu Jin

    1. University of Surrey, Guildford, United Kingdom

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  7. Christian Grimme

    1. University of Münster, Münster, Germany

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10173)

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

Included in the following conference series:

Conference proceedings info: EMO 2017.

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Table of contents (46 papers)

  1. Front Matter

    Pages I-XIV
    Download chapter PDF

  2. On the Effect of Scalarising Norm Choice in a ParEGO implementation

    • Naveed Reza Aghamohammadi, Shaul Salomon, Yiming Yan, Robin C. Purshouse
    Pages 1-15

  3. Multi-objective Big Data Optimization with jMetal and Spark

    • Cristóbal Barba-Gonzaléz, José García-Nieto, Antonio J. Nebro, José F. Aldana-Montes
    Pages 16-30

  4. An Empirical Assessment of the Properties of Inverted Generational Distance on Multi- and Many-Objective Optimization

    • Leonardo C. T. Bezerra, Manuel López-Ibáñez, Thomas Stützle
    Pages 31-45

  5. Solving the Bi-objective Traveling Thief Problem with Multi-objective Evolutionary Algorithms

    • Julian Blank, Kalyanmoy Deb, Sanaz Mostaghim
    Pages 46-60

  6. Automatically Configuring Multi-objective Local Search Using Multi-objective Optimisation

    • Aymeric Blot, Alexis Pernet, Laetitia Jourdan, Marie-Éléonore Kessaci-Marmion, Holger H. Hoos
    Pages 61-76

  7. The Multiobjective Shortest Path Problem Is NP-Hard, or Is It?

    • Fritz Bökler
    Pages 77-87

  8. Angle-Based Preference Models in Multi-objective Optimization

    • Marlon Braun, Pradyumn Shukla, Hartmut Schmeck
    Pages 88-102

  9. Quantitative Performance Assessment of Multiobjective Optimizers: The Average Runtime Attainment Function

    • Dimo Brockhoff, Anne Auger, Nikolaus Hansen, Tea Tušar
    Pages 103-119

  10. A Multiobjective Strategy to Allocate Roadside Units in a Vehicular Network with Guaranteed Levels of Service

    • Flávio Vinícius Cruzeiro Martins, João F. M. Sarubbi, Elizabeth F. Wanner
    Pages 120-134

  11. An Approach for the Local Exploration of Discrete Many Objective Optimization Problems

    • Oliver Cuate, Bilel Derbel, Arnaud Liefooghe, El-Ghazali Talbi, Oliver Schütze
    Pages 135-150

  12. A Note on the Detection of Outliers in a Binary Outranking Relation

    • Yves De Smet, Jean-Philippe Hubinont, Jean Rosenfeld
    Pages 151-159

  13. Classifying Metamodeling Methods for Evolutionary Multi-objective Optimization: First Results

    • Kalyanmoy Deb, Rayan Hussein, Proteek Roy, Gregorio Toscano
    Pages 160-175

  14. Weighted Stress Function Method for Multiobjective Evolutionary Algorithm Based on Decomposition

    • Roman Denysiuk, António Gaspar-Cunha
    Pages 176-190

  15. Timing the Decision Support for Real-World Many-Objective Optimization Problems

    • João A. Duro, Dhish Kumar Saxena
    Pages 191-205

  16. On the Influence of Altering the Action Set on PROMETHEE II’s Relative Ranks

    • Stefan Eppe, Yves De Smet
    Pages 206-220

  17. Peek – Shape – Grab: A Methodology in Three Stages for Approximating the Non-dominated Points of Multiobjective Discrete/Combinatorial Optimization Problems with a Multiobjective Metaheuristic

    • Xavier Gandibleux
    Pages 221-235

  18. A New Reduced-Length Genetic Representation for Evolutionary Multiobjective Clustering

    • Mario Garza-Fabre, Julia Handl, Joshua Knowles
    Pages 236-251

  19. A Fast Incremental BSP Tree Archive for Non-dominated Points

    • Tobias Glasmachers
    Pages 252-266

  20. Adaptive Operator Selection for Many-Objective Optimization with NSGA-III

    • Richard A. Gonçalves, Lucas M. Pavelski, Carolina P. de Almeida, Josiel N. Kuk, Sandra M. Venske, Myriam R. Delgado
    Pages 267-281
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Other volumes

  1. Evolutionary Multi-Criterion Optimization

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About this book

This book constitutes the refereed proceedings of the 9th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2017 held in Münster, Germany in March 2017. 

The 33 revised full papers presented together with 13 poster presentations were carefully reviewed and selected from 72 submissions. The EMO 2017 aims to discuss all aspects of EMO development and deployment, including theoretical foundations; constraint handling techniques; preference handling techniques; handling of continuous, combinatorial or mixed-integer problems; local search techniques; hybrid approaches; stopping criteria; parallel EMO models; performance evaluation; test functions and benchmark problems; algorithm selection approaches; many-objective optimization; large scale optimization; real-world applications; EMO algorithm implementations.

Editors and Affiliations

  • University of Münster, Münster, Germany

    Heike Trautmann, Christian Grimme

  • TU Dortmund University, Dortmund, Germany

    Günter Rudolph

  • University of Wuppertal, Wuppertal, Germany

    Kathrin Klamroth

  • CINVESTAV-IPN, Mexico City, Mexico

    Oliver Schütze

  • Clemson University, Clemson, USA

    Margaret Wiecek

  • University of Surrey, Guildford, United Kingdom

    Yaochu Jin

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