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Evolutionary Multi-Criterion Optimization

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

  • Heike Trautmann
  • Günter Rudolph
  • Kathrin Klamroth
  • Oliver Schütze
  • Margaret Wiecek
  • Yaochu Jin
  • Christian Grimme

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

Also part of the Theoretical Computer Science and General Issues book sub series (LNTCS, volume 10173)

Table of contents

  1. Front Matter
    Pages I-XIV
  2. Naveed Reza Aghamohammadi, Shaul Salomon, Yiming Yan, Robin C. Purshouse
    Pages 1-15
  3. Cristóbal Barba-Gonzaléz, José García-Nieto, Antonio J. Nebro, José F. Aldana-Montes
    Pages 16-30
  4. Leonardo C. T. Bezerra, Manuel López-Ibáñez, Thomas Stützle
    Pages 31-45
  5. Aymeric Blot, Alexis Pernet, Laetitia Jourdan, Marie-Éléonore Kessaci-Marmion, Holger H. Hoos
    Pages 61-76
  6. Marlon Braun, Pradyumn Shukla, Hartmut Schmeck
    Pages 88-102
  7. Dimo Brockhoff, Anne Auger, Nikolaus Hansen, Tea Tušar
    Pages 103-119
  8. Flávio Vinícius Cruzeiro Martins, João F. M. Sarubbi, Elizabeth F. Wanner
    Pages 120-134
  9. Oliver Cuate, Bilel Derbel, Arnaud Liefooghe, El-Ghazali Talbi, Oliver Schütze
    Pages 135-150
  10. Yves De Smet, Jean-Philippe Hubinont, Jean Rosenfeld
    Pages 151-159
  11. Kalyanmoy Deb, Rayan Hussein, Proteek Roy, Gregorio Toscano
    Pages 160-175
  12. Mario Garza-Fabre, Julia Handl, Joshua Knowles
    Pages 236-251
  13. Richard A. Gonçalves, Lucas M. Pavelski, Carolina P. de Almeida, Josiel N. Kuk, Sandra M. Venske, Myriam R. Delgado
    Pages 267-281
  14. Jussi Hakanen, Joshua D. Knowles
    Pages 282-297
  15. Daniel Horn, Melanie Dagge, Xudong Sun, Bernd Bischl
    Pages 298-313
  16. Amin Ibrahim, Shahryar Rahnamayan, Miguel Vargas Martin, Kalyanmoy Deb
    Pages 314-328
  17. Pascal Kerschke, Christian Grimme
    Pages 329-343
  18. Marie-Eléonore Kessaci-Marmion, Clarisse Dhaenens, Jérémie Humeau
    Pages 344-358
  19. Ahmed Khalifa, Mike Preuss, Julian Togelius
    Pages 359-374
  20. Longmei Li, Iryna Yevseyeva, Vitor Basto-Fernandes, Heike Trautmann, Ning Jing, Michael Emmerich
    Pages 406-421
  21. Arnaud Liefooghe, Bilel Derbel, Sébastien Verel, Hernán Aguirre, Kiyoshi Tanaka
    Pages 422-437
  22. Renan Mendes, Elizabeth Wanner, Flávio Martins, João Sarubbi
    Pages 438-452
  23. Ana Amélia S. Pereira, Helio J. C. Barbosa, Heder S. Bernardino
    Pages 484-498
  24. Miriam Pescador-Rojas, Raquel Hernández Gómez, Elizabeth Montero, Nicolás Rojas-Morales, María-Cristina Riff, Carlos A. Coello Coello
    Pages 499-513
  25. Andreas Richter, Jascha Achenbach, Stefan Menzel, Mario Botsch
    Pages 514-528
  26. Haitham Seada, Mohamed Abouhawwash, Kalyanmoy Deb
    Pages 545-559
  27. Olivier Sobrie, Vincent Mousseau, Marc Pirlot
    Pages 575-589
  28. A. K. M. Khaled Ahsan Talukder, Kalyanmoy Deb, Shahryar Rahnamayan
    Pages 590-605
  29. Kevin Tierney, Joshua Handali, Christian Grimme, Heike Trautmann
    Pages 622-638
  30. Vanessa Volz, Günter Rudolph, Boris Naujoks
    Pages 639-653
  31. Hao Wang, André Deutz, Thomas Bäck, Michael Emmerich
    Pages 654-669
  32. Simon Wessing, Rosa Pink, Kai Brandenbusch, Günter Rudolph
    Pages 670-684
  33. Kaifeng Yang, Michael Emmerich, André Deutz, Carlos M. Fonseca
    Pages 685-700
  34. Back Matter
    Pages 701-702

About these proceedings

Introduction

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.

Keywords

big data evolutionary algorithms machine learning numeric computing parallel computing algorithm analysis and problem complexity artificial intelligence cluster analysis combinatoric problems computer applications evolutionary computation expert knowledge integration hybrid optimization model-based optimization multi-criteria decision making multi-objective optimization performance evaluation quality of service randomized search heuristics visualization

Editors and affiliations

  • Heike Trautmann
    • 1
  • Günter Rudolph
    • 2
  • Kathrin Klamroth
    • 3
  • Oliver Schütze
    • 4
  • Margaret Wiecek
    • 5
  • Yaochu Jin
    • 6
  • Christian Grimme
    • 7
  1. 1.University of MünsterMünsterGermany
  2. 2.TU Dortmund UniversityDortmundGermany
  3. 3.University of WuppertalWuppertalGermany
  4. 4.CINVESTAV-IPNMexico CityMexico
  5. 5.Clemson UniversityClemsonUSA
  6. 6.University of SurreyGuildfordUnited Kingdom
  7. 7.University of MünsterMünsterGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-54157-0
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-54156-3
  • Online ISBN 978-3-319-54157-0
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site