Keywords: Evolutionary Computation [rss]
2015
[25] Evolutionary Computation and Constraint Satisfaction (J. van Hemert), Chapter in Handbook of Computational Intelligence (J. Kacpryk, W. Pedrycz, eds.), Springer, 2015. [bib] [doi]
2009
[24] The Evolutionary Transition Algorithm: Evolving Complex Solutions out of Simpler Ones (T. Lenaerts, A. Defaweux, J.I. van Hemert), Chapter in Nature-Inspired Algorithms for Optimisation (Raymond Chiong, ed.), Springer, volume 193, 2009. [bib]
2008
[23] Contraction-Based Heuristics to Improve the Efficiency of Algorithms Solving the Graph Colouring Problem (I. Juhos, J.I. van Hemert), Chapter in Recent Advances in Evolutionary Computation for Combinatorial Optimization (C. Cotta, J.I. van Hemert, eds.), Springer, 2008. [bib]
[22] Graph Colouring Heuristics Guided by Higher Order Graph Properties (I. Juhos, J.I. van Hemert), In Evolutionary Computation in Combinatorial Optimization (J. van Hemert, C. Cotta, eds.), Springer, volume 4972, 2008. [bib]
[21] European Graduate Student Workshop on Evolutionary Computation, (C. Di Chio, M. Giacobini, J.I. van Hemert, eds.), 2008. [bib]
[20] Evolutionary Computation in Combinatorial Optimization, 8th European Conference, (J.I. van Hemert, C. Cotta, eds.), Springer, volume LNCS 4972, 2008. [bib] [pdf]
[19] Recent Advances in Evolutionary Computation for Combinatorial Optimization (C. Cotta, J.I. van Hemert), Springer, volume 153, 2008. [bib]
2007
[18] European Graduate Student Workshop on Evolutionary Computation, (M. Giacobini, J.I. van Hemert, eds.), 2007. [bib]
[17] Evolutionary Computation in Combinatorial Optimization, 7th European Conference, (C. Cotta, J.I. van Hemert, eds.), Springer, volume LNCS 4446, 2007. [bib] [pdf]
2006
[16] Evolving combinatorial problem instances that are difficult to solve (J.I. van Hemert), In Evolutionary Computation, volume 14, 2006. [bib] [pdf]
[15] Neighborhood Searches for the Bounded Diameter Minimum Spanning Tree Problem Embedded in a VNS, EA, and ACO (M. Gruber, J.I. van Hemert, G.R. Raidl), In Proceedings of the Genetic and Evolutionary Computation Conference (Maarten Keijzer et al., ed.), ACM, volume 2, 2006. [bib] [pdf]
[14] European Graduate Student Workshop on Evolutionary Computation, (M. Giacobini, J.I. van Hemert, eds.), 2006. [bib]
2005
[13] Genetic Programming, Proceedings of the 8th European Conference, (M. Keijzer, A. Tettamanzi, P. Collet, J. van Hemert, M. Tomassini, eds.), Springer, volume 3447, 2005. [bib] [pdf]
[12] Complexity Transitions in Evolutionary Algorithms: Evaluating the impact of the initial population (A. Defaweux, T. Lenaerts, J.I. van Hemert, J. Parent), In Proceedings of the Congress on Evolutionary Computation, IEEE Press, 2005. [bib]
[11] Transition Models as an incremental approach for problem solving in Evolutionary Algorithms (A. Defaweux, T. Lenaerts, J.I. van Hemert, J. Parent), In Proceedings of the Genetic and Evolutionary Computation Conference (H.-G. Beyer et al., ed.), ACM Press, 2005. [bib] [pdf]
[10] Evolutionary Transitions as a Metaphor for Evolutionary Optimization (A. Defaweux, T. Lenaerts, J.I. van Hemert), In Advances in Artificial Life (M. Capcarrere, A.A. Freitas, P.J. Bentley, C.G. Johnson, J. Timmis, eds.), Springer, 2005. [bib]
2004
[9] Phase transition properties of clustered travelling salesman problem instances generated with evolutionary computation (J.I. van Hemert, N.B. Urquhart), In Parallel Problem Solving from Nature (Xin Yao, Edmund Burke, Jose A. Lozano, Jim Smith, Juan J. Merelo-Guervós, John A. Bullinaria, Jonathan Rowe, Peter Ti\vno Ata Kabán, Hans-Paul Schwefel, eds.), Springer, volume 3242, 2004. [bib] [pdf]
[8] A Study into Ant Colony Optimization, Evolutionary Computation and Constraint Programming on Binary Constraint Satisfaction Problems (J.I. van Hemert, C. Solnon), In Evolutionary Computation in Combinatorial Optimization (J. Gottlieb, G. Raidl, eds.), Springer, 2004. [bib]
[7] Dynamic Routing Problems with Fruitful Regions: Models and Evolutionary Computation (J.I. van Hemert, J.A. la Poutré), In Parallel Problem Solving from Nature (Xin Yao, Edmund Burke, Jose A. Lozano, Jim Smith, Juan J. Merelo-Guervós, John A. Bullinaria, Jonathan Rowe, Peter Ti\vno Ata Kabán, Hans-Paul Schwefel, eds.), Springer, volume 3242, 2004. [bib]
[6] Robust parameter settings for variation operators by measuring the resampling ratio: A study on binary constraint satisfaction problems (J.I. van Hemert, T. Bäck), In Journal of Heuristics, volume 10, 2004. [bib]
2002
[5] Measuring the Searched Space to Guide Efficiency: The Principle and Evidence on Constraint Satisfaction (J.I. van Hemert, T. Bäck), In Parallel Problem Solving from Nature (J.J. Merelo, A. Panagiotis, H.-G. Beyer, José-Luis Fernández-Villacañas, Hans-Paul Schwefel, eds.), Springer, 2002. [bib]
2000
[4] Stepwise Adaptation of Weights for Symbolic Regression with Genetic Programming (J. Eggermont, J.I. van Hemert), In Proceedings of the Twelfth Belgium/Netherlands Conference on Artificial Intelligence (A. van den Bosch, H. Weigand, eds.), 2000. [bib]
1999
[3] Comparing genetic programming variants for data classification (J. Eggermont, A.E. Eiben, J.I. van Hemert), In Proceedings of the Eleventh Belgium/Netherlands Conference on Artificial Intelligence (E. Postma, M. Gyssens, eds.), 1999. [bib]
[2] A comparison of genetic programming variants for data classification (J. Eggermont, A.E. Eiben, J.I. van Hemert), In Advances in Intelligent Data Analysis (D.J. Hand, J.N. Kok, M.R. Berthold, eds.), Springer, 1999. [bib]
[1] Adapting the Fitness Function in GP for Data Mining (J. Eggermont, A.E. Eiben, J.I. van Hemert), In Genetic Programming (R. Poli, P. Nordin, W.B. Langdon, T.C. Fogarty, eds.), Springer, 1999. [bib]
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