© 2012

Evolutionary Computation in Combinatorial Optimization

12th European Conference, EvoCOP 2012, Málaga, Spain, April 11-13, 2012. Proceedings

  • Jin-Kao Hao
  • Martin Middendorf
Conference proceedings EvoCOP 2012

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7245)

Table of contents

  1. Front Matter
  2. Martin Schwengerer, Sandro Pirkwieser, Günther R. Raidl
    Pages 13-24
  3. Thais Ávila, Ángel Corberán, Isaac Plana, José M. Sanchis
    Pages 25-36
  4. Jaber Jemai, Manel Zekri, Khaled Mellouli
    Pages 37-48
  5. Rudinei Martins de Oliveira, Geraldo Regis Mauri, Luiz Antonio Nogueira Lorena
    Pages 49-62
  6. Noura Al Moubayed, Andrei Petrovski, John McCall
    Pages 75-86
  7. Mohsen Rahmani, Ruben A. Romero, Marcos J. Rider, Miguel Paredes
    Pages 87-98
  8. Florian Allerding, Marc Premm, Pradyumn Kumar Shukla, Hartmut Schmeck
    Pages 99-110
  9. Marco Gavanelli, Maddalena Nonato, Andrea Peano, Stefano Alvisi, Marco Franchini
    Pages 124-135
  10. Gabriela Ochoa, Matthew Hyde, Tim Curtois, Jose A. Vazquez-Rodriguez, James Walker, Michel Gendreau et al.
    Pages 136-147
  11. Francisco J. Rodriguez, Christian Blum, Manuel Lozano, Carlos García-Martínez
    Pages 172-181
  12. Mario Garza-Fabre, Eduardo Rodriguez-Tello, Gregorio Toscano-Pulido
    Pages 182-193
  13. Wahabou Abdou, Christelle Bloch, Damien Charlet, François Spies
    Pages 194-205
  14. Jérémie Dubois-Lacoste, Manuel López-Ibáñez, Thomas Stützle
    Pages 206-217
  15. Jun He, Feidun He, Hongbin Dong
    Pages 218-229

About these proceedings


This book constitutes the refereed proceedings of the 12th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2012, held in Málaga, Spain, in April 2012, colocated with the Evo* 2012 events EuroGP, EvoBIO, EvoMUSART, and EvoApplications. . The 22 revised full papers presented were carefully reviewed and selected from 48 submissions. The papers present the latest research and discuss current developments and applications in metaheuristics - a paradigm to effectively solve difficult combinatorial optimization problems appearing in various industrial, economic, and scientific domains. Prominent examples of metaheuristics are evolutionary algorithms, simulated annealing, tabu search, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, estimation of distribution algorithms, and ant colony optimization.


evolutionary algorithm genetic algorithm hyper-heuristic multi-objective optimization stochastic optimization

Editors and affiliations

  • Jin-Kao Hao
    • 1
  • Martin Middendorf
    • 2
  1. 1.Faculty of AngersUniversity of AngersAngers Cedex 01France
  2. 2.Department of Computer ScienceUniversity of LeipzigLeipzigGermany

Bibliographic information