Evolutionary Computation in Combinatorial Optimization

1. Front Matter

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2. A Methodology for Comparing the Execution Time of Metaheuristics Running on Different Hardware

   • Julián Domínguez, Enrique Alba

   Pages 1-12

3. A Variable Neighborhood Search Approach for the Two-Echelon Location-Routing Problem

   • Martin Schwengerer, Sandro Pirkwieser, Günther R. Raidl

   Pages 13-24

4. An ILS-Based Metaheuristic for the Stacker Crane Problem

   • Thais Ávila, Ángel Corberán, Isaac Plana, José M. Sanchis

   Pages 25-36

5. An NSGA-II Algorithm for the Green Vehicle Routing Problem

   • Jaber Jemai, Manel Zekri, Khaled Mellouli

   Pages 37-48

6. Clustering Search Heuristic for Solving a Continuous Berth Allocation Problem

   • Rudinei Martins de Oliveira, Geraldo Regis Mauri, Luiz Antonio Nogueira Lorena

   Pages 49-62

7. Combining Heuristic and Exact Methods to Solve the Vehicle Routing Problem with Pickups, Deliveries and Time Windows

   • Penny L. Holborn, Jonathan M. Thompson, Rhyd Lewis

   Pages 63-74

8. D ² MOPSO: Multi-Objective Particle Swarm Optimizer Based on Decomposition and Dominance

   • Noura Al Moubayed, Andrei Petrovski, John McCall

   Pages 75-86

9. Domain Reduction Using GRASP Construction Phase for Transmission Expansion Planning Problem

   • Mohsen Rahmani, Ruben A. Romero, Marcos J. Rider, Miguel Paredes

   Pages 87-98

10. Electrical Load Management in Smart Homes Using Evolutionary Algorithms

    • Florian Allerding, Marc Premm, Pradyumn Kumar Shukla, Hartmut Schmeck

    Pages 99-110

11. Exact Computation of the Fitness-Distance Correlation for Pseudoboolean Functions with One Global Optimum

    • Francisco Chicano, Enrique Alba

    Pages 111-123

12. Genetic Algorithms for Scheduling Devices Operation in a Water Distribution System in Response to Contamination Events

    • Marco Gavanelli, Maddalena Nonato, Andrea Peano, Stefano Alvisi, Marco Franchini

    Pages 124-135

13. HyFlex: A Benchmark Framework for Cross-Domain Heuristic Search

    • Gabriela Ochoa, Matthew Hyde, Tim Curtois, Jose A. Vazquez-Rodriguez, James Walker, Michel Gendreau et al.

    Pages 136-147

14. Hyper-Heuristic Based on Iterated Local Search Driven by Evolutionary Algorithm

    • Jiří Kubalík

    Pages 148-159

15. Intensification/Diversification-Driven ILS for a Graph Coloring Problem

    • Samir Loudni

    Pages 160-171

16. Iterated Greedy Algorithms for the Maximal Covering Location Problem

    • Francisco J. Rodriguez, Christian Blum, Manuel Lozano, Carlos García-Martínez

    Pages 172-181

17. Multiobjectivizing the HP Model for Protein Structure Prediction

    • Mario Garza-Fabre, Eduardo Rodriguez-Tello, Gregorio Toscano-Pulido

    Pages 182-193

18. Multi-Pareto-Ranking Evolutionary Algorithm

    • Wahabou Abdou, Christelle Bloch, Damien Charlet, François Spies

    Pages 194-205

19. Pareto Local Search Algorithms for Anytime Bi-objective Optimization

    • Jérémie Dubois-Lacoste, Manuel López-Ibáñez, Thomas Stützle

    Pages 206-217

20. Pure Strategy or Mixed Strategy?

    • Jun He, Feidun He, Hongbin Dong

    Pages 218-229

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
• algorithm analysis and problem complexity

• Faculty of Angers, University of Angers, Angers Cedex 01, France

  Jin-Kao Hao

• Department of Computer Science, University of Leipzig, Leipzig, Germany

  Martin Middendorf

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