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A. Barker, Weissman, J., and van Hemert, J. I., The Circulate Architecture: Avoiding Workflow Bottlenecks Caused By Centralised Orchestration, Cluster Computing, vol. 12, p. 221--235, 2009.
J. I. van Hemert, Comparing Classical Methods for Solving Binary Constraint Satisfaction Problems with State of the Art Evolutionary Computation, in Springer Lecture Notes on Computer Science, 2002, p. 81--90.
B. G. W. Craenen, Eiben, A. E., and van Hemert, J. I., Comparing Evolutionary Algorithms on Binary Constraint Satisfaction Problems, IEEE Transactions on Evolutionary Computation, vol. 7, p. 424--444, 2003.
J. Eggermont, Eiben, A. E., and van Hemert, J. I., Comparing genetic programming variants for data classification, in Proceedings of the Eleventh Belgium/Netherlands Conference on Artificial Intelligence (BNAIC'99), 1999, p. 253--254.
J. Eggermont, Eiben, A. E., and van Hemert, J. I., A comparison of genetic programming variants for data classification, in Springer Lecture Notes on Computer Science, 1999, p. 281--290.
A. Defaweux, Lenaerts, T., van Hemert, J. I., and Parent, J., Complexity Transitions in Evolutionary Algorithms: Evaluating the impact of the initial population, in Proceedings of the Congress on Evolutionary Computation, 2005, p. 196--203.
J. I. van Hemert, Constraint Satisfaction Problems and Evolutionary Algorithms: A Reality Check, in Proceedings of the Twelfth Belgium/Netherlands Conference on Artificial Intelligence (BNAIC'00), 2000, p. 267--274.
I. Juhos and van Hemert, J. I., Contraction-Based Heuristics to Improve the Efficiency of Algorithms Solving the Graph Colouring Problem, in Studies in Computational Intelligence, C. Cotta and van Hemert, J. I., Eds. Springer, 2008, p. 167--184.
I. Juhos and van Hemert, J. I., Contraction-Based Heuristics to Improve the Efficiency of Algorithms Solving the Graph Colouring Problem, in Studies in Computational Intelligence, C. Cotta and van Hemert, J. I., Eds. Springer, 2008, p. 167--184.
R. R. Kitchen, Sabine, V. S., Sims, A. H., Macaskill, E. J., Renshaw, L., Thomas, J. S., van Hemert, J. I., Dixon, J. M., and Bartlett, J. M. S., Correcting for intra-experiment variation in Illumina BeadChip data is necessary to generate robust gene-expression profiles, BMC Genomics, vol. 11, no. 134, 2010.
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J. I. van Hemert and Jansen, M. L. M., An Engineering Approach to Evolutionary Art, in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), 2001, p. 177.
J. I. van Hemert, Evolutionary Computation in Constraint Satisfaction and Machine Learning --- An abstract of my PhD., in Proceedings of the Brussels Evolutionary Algorithms Day (BEAD-2001), 2001.
A. Defaweux, Lenaerts, T., and van Hemert, J. I., Evolutionary Transitions as a Metaphor for Evolutionary Optimization, in LNAI 3630, 2005, p. 342--352.
J. I. van Hemert, Evolving binary constraint satisfaction problem instances that are difficult to solve, in Proceedings of the IEEE 2003 Congress on Evolutionary Computation, 2003, p. 1267--1273.
J. I. van Hemert, Evolving combinatorial problem instances that are difficult to solve, Evolutionary Computation, vol. 14, p. 433--462, 2006.
J. I. van Hemert and la Poutré, J. A., Exploiting Fruitful Regions in Dynamic Routing using Evolutionary Computation, in Studies in Computational Intelligence , vol. 161, F. Pereira Babtista and Tavares, J., Eds. Springer, 2009, p. 131--149.
A. E. Eiben, van Hemert, J. I., Marchiori, E., and Steenbeek, A. G., Extended abstract: Solving Binary Constraint Satisfaction Problems using Evolutionary Algorithms with an Adaptive Fitness Function, in Proceedings of the Xth Netherlands/Belgium Conference on Artificial Intelligence (NAIC'98), 1998, p. 299--301.
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J. I. van Hemert, Van Hoyweghen, C., Lukschandl, E., and Verbeeck, K., A ``Futurist'' approach to dynamic environments, in Proceedings of the Workshops at the Genetic and Evolutionary Computation Conference, Dynamic Optimization Problems, 2001, p. 35--38.

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