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Academic Publications

| Journal Papers | Conference and Workshop Papers | Books | Book Chapters | Edited Books | Patents | Technical Reports | Dissertation and Thesis |

Journal Papers
  1. Chen, Y.-p., & Chen, C.-H. (2009). Enabling the extended compact genetic algorithm for real-parameter optimization by using adaptive discretization. Evolutionary Computation, N/A(N/A), N/A–N/A. (SCI, accepted).

  2. Chen, Y.-p., Peng, W.-C., & Jian, M.-c. (2007). Particle swarm optimization with recombination and dynamic linkage discovery. IEEE Transactions on Systems, Man, and Cybernetics–Part B: Cybernetics, 37(6), 1460–1470. (SCI).

  3. Chen, Y.-p., & Goldberg, D. E. (2005). Convergence time for the linkage learning genetic algorithm. Evolutionary Computation, 13(3), 279–302. (SCI).

  4. Chen, Y.-p., & Goldberg, D. E. (2004). Introducing subchromosome representations to the linkage learning genetic algorithms. Lecture Notes in Computer Science (LNCS), 3102, 971–982.

  5. Ohnishi, K., Sastry, K., Chen, Y.-p., & Goldberg, D. E. (2004). Inducing sequentiality using grammatical genetic codes. Lecture Notes in Computer Science (LNCS), 3102, 1426–1437.

  6. Llorà, X., Ohnishi, K., Chen, Y.-p., Goldberg, D. E., & Welge, M. E. (2004). Enhanced innovation: A fusion of chance discovery and evolutionary computation to foster creative processes and decision making. Lecture Notes in Computer Science (LNCS), 3103, 1314–1315.

  7. Chen, Y.-p., & Goldberg, D. E. (2003a). An analysis of a reordering operator with tournament selection on a GA-hard problem. Lecture Notes in Computer Science (LNCS), 2723, 825–836.

  8. Chen, Y.-p., & Goldberg, D. E. (2003b). Tightness time for the linkage learning genetic algorithm. Lecture Notes in Computer Science (LNCS), 2723, 837–849.

  9. Yu, T.-L., Goldberg, D. E., Yassine, A. A., & Chen, Y.-p. (2003). A genetic algorithm design inspired by organizational theory: A pilot study of a dependency structure matrix driven genetic algorithm. Lecture Notes in Computer Science (LNCS), 2724, 1620–1621.

  10. Chen, Y.-p., & Goldberg, D. E. (2002). Introducing start expression genes to the linkage learning genetic algorithm. Lecture Notes in Computer Science (LNCS), 2439, 351–360.

  11. Horng, J.-T., Chen, Y.-p., & Kao, C.-Y. (2001). A theoretical aspect of a stochastic sketching method for global optimization. Journal of Information Science and Engineering (JISE), 17(1), 47–71. (SCI).

  12. Chen, Y.-p., Horng, J.-T., & Kao, C.-Y. (1999). Stochastic sketching: A new method for global optimization. Soft Computing, 3(2), 101–110. (SCI).

  13. Yang, J.-M., Chen, Y.-p., Horng, J.-T., & Kao, C.-Y. (1997). Applying family competition to evolution strategies for constrained optimization. Lecture Notes in Computer Science (LNCS), 1213, 201–211. (EI).

Conference and Workshop Papers
  1. Chuang, C.-Y., & Chen, Y.-p. (2008a). Recognizing problem decomposition with inductive linkage identification: Population requirement vs. subproblem complexity. In Proceedings of the Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems (SCIS & ISIS 2008) (pp. N/A–N/A). (Invited).

  2. Chuang, C.-Y., & Chen, Y.-p. (2008b). On the effectiveness of distributions estimated by probabilistic model building. In Proceedings of ACM SIGEVO Genetic and Evolutionary Computation Conference 2008 (GECCO-2008) (pp. 391–398). (EI).

  3. Liou, J.-J., & Chen, Y.-p. (2008). Adaptive discretization on multidimensional continuous search spaces. In Proceedings of ACM SIGEVO Genetic and Evolutionary Computation Conference 2008 (GECCO-2008) (pp. 977–984). (EI).

  4. Chuang, C.-Y., & Chen, Y.-p. (2007). Linkage identification by perturbation and decision tree induction. In Proceedings of 2007 IEEE Congress on Evolutionary Computation (CEC 2007) (pp. 357–363). (EI).

  5. Lin, Y.-y., & Chen, Y.-p. (2007). Crowd control with swarm intelligence. In Proceedings of 2007 IEEE Congress on Evolutionary Computation (CEC 2007) (pp. 3321–3328). (EI).

  6. Hsieh, C.-T., Chen, C.-M., & Chen, Y.-p. (2007). Particle swarm guided evolution strategy. In Proceedings of ACM SIGEVO Genetic and Evolutionary Computation Conference 2007 (GECCO-2007) (pp. 650–657). (EI).

  7. Chen, H.-W., & Chen, Y.-p. (2007a). Introducing fault tolerance to XCS. In Proceedings of ACM SIGEVO Genetic and Evolutionary Computation Conference 2007 (GECCO-2007) (pp. 1871). (EI).

  8. Chen, C.-H., & Chen, Y.-p. (2007b). Real-coded ECGA for economic dispatch. In Proceedings of ACM SIGEVO Genetic and Evolutionary Computation Conference 2007 (GECCO-2007) (pp. 1920–1927). (EI).

  9. Hung, P.-C., Chen, Y.-p., & Zan, H. W. (2007). Characteristic determination for solid state devices with evolutionary computation: A case study. In Proceedings of ACM SIGEVO Genetic and Evolutionary Computation Conference 2007 (GECCO-2007) (pp. 2029–2036). (EI).

  10. Jian, M.-C., & Chen, Y.-p. (2006). Introducing recombination with dynamic linkage discovery to particle swarm optimization. In Proceedings of ACM SIGEVO Genetic and Evolutionary Computation Conference 2006 (GECCO-2006) (pp. 85–86). (EI).

  11. Chen, C.-H., Liu, W.-N., & Chen, Y.-p. (2006). Adaptive discretization for probabilistic model building genetic algorithms. In Proceedings of ACM SIGEVO Genetic and Evolutionary Computation Conference 2006 (GECCO-2006) (pp. 1103–1110). (EI).

  12. Hung, P.-C., & Chen, Y.-p. (2006). iECGA: Integer extended compact genetic algorithm. In Proceedings of ACM SIGEVO Genetic and Evolutionary Computation Conference 2006 (GECCO-2006) (pp. 1415–1416). (EI).

  13. Chen, H.-W., & Chen, Y.-p. (2006). FTXI: Fault tolerance XCS in integer. In Proceedings of ACM SIGEVO Genetic and Evolutionary Computation Conference 2006 (GECCO-2006) (pp. 1589–1590). (EI).

  14. Fu, D.-Y., Wu, T.-Y., Chen, C.-T., Wu, K.-C., & Chen, Y.-p. (2006). Evolutionary interactive music composition. In Proceedings of ACM SIGEVO Genetic and Evolutionary Computation Conference 2006 (GECCO-2006) (pp. 1863–1864). (EI).

  15. Chen, Y.-p., & Goldberg, D. E. (2004). Convergence time for the linkage learning genetic algorithm. In Proceedings of 2004 IEEE Congress on Evolutionary Computation (CEC 2004) (pp. 39–46). (EI).

  16. Yu, T.-L., Chen, Y.-p., Goldberg, D. E., & Chen, J.-H. (2003). An adaptive sampling scheme for genetic algorithms on the sampled OneMax problem. In Proceedings of Artificial Neural Networks in Engineering 2003 (ANNIE 2003) (pp. 39–44). (EI).

  17. Yu, T.-L., Goldberg, D. E., Yassine, A. A., & Chen, Y.-p. (2003). Genetic algorithm design inspired by organizational theory: Pilot study of a dependency structure matrix driven genetic algorithm. In Proceedings of Artificial Neural Networks in Engineering 2003 (ANNIE 2003) (pp. 327–332). (EI).

  18. Chen, Y.-p. (2002). Using start expression genes for building-block separation in the linkage learning genetic algorithm. In Proceedings of Genetic and Evolutionary Computation Conference 2002 (GECCO-2002) (pp. 268–271). (Graduate student workshop).

  19. Singh, A., Goldberg, D. E., & Chen, Y.-p. (2002a). Modified linkage learning genetic algorithm for difficult non-stationary problems. In Proceedings of Genetic and Evolutionary Computation Conference 2002 (GECCO-2002) (pp. 699). (Poster session).

  20. Singh, A., Goldberg, D. E., & Chen, Y.-p. (2002b). Modified linkage learning genetic algorithm for difficult non-stationary problems. In Proceedings of Genetic and Evolutionary Computation Conference 2002 (GECCO-2002) (pp. 419–426). (Late-breaking Papers).

  21. Jih, W.-r., Chen, Y.-p., & Hsu, J. (1996). A comparative study of genetic algorithms for vehicle routing with time constraints. In Proceedings of International Conference on Artificial Intelligence (pp. 17–24). Kaohsiung, Taiwan: National Sun Yat-Sen University.

Books
  1. Chen, Y.-p. (2005). Extending the scalability of linkage learning genetic algorithms: Theory and practice, Volume 190 of Studies in Fuzziness and Soft Computing. Springer. ISBN: 3-540-28459-1. Erratum Springer Link Amazon Link.

Book Chapters
  1. Sinha, A., Chen, Y.-p., & Goldberg, D. E. (2004). Designing efficient genetic and evolutionary algorithm hybrids. In Hart, W. E., Krasnogor, N., & Smith, J. (Eds.), Recent Advances in Memetic Algorithms, Volume 166 of Studies in Fuzziness and Soft Computing (pp. 259–288). Springer. ISBN: 3-540-22904-3. Springer Link.

Edited Books
  1. Chen, Y.-p., & Lim, M.-H. (Eds.) (2008). Linkage in evolutionary computation, Volume 157 of Studies in Computational Intelligence. Springer. ISBN: 978-3-540-85067-0. Springer Link Amazon Link.

Patents
  1. Chen, Y.-p., Wu, K.-C., Wu, T.-Y., Fu, D.-y., & Chen, C.-T. (2007). Method and system for automatic music composition. Taiwan Invention Patent No. I285880, Issued at August 21, 2007.

Technical Reports
  1. Tang, K., Yao, X., Suganthan, P. N., MacNish, C., Chen, Y.-p., Chen, C.-M., & Yang, Z. (2007). Benchmark functions for the CEC'2008 special session and competition on large scale global optimization (Technical Report). Nature Inspired Computation and Applications Laboratory, University of Science and Technology of China. Download.

  2. Chen, Y.-p., Yu, T.-L., Sastry, K., & Goldberg, D. E. (2007). A survey of genetic linkage learning techniques (Technical Report 2007014). Urbana, Illinois, USA: Illinois Genetic Algorithms Laboratory, Department of General Engineering, University of Illinois at Urbana-Champaign. Download.

  3. Suganthan, P. N., Hansen, N., Liang, J. J., Deb, K., Chen, Y.-p., Auger, A., & Tiwari, S. (2005). Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization (Technical Report 2005001). HsinChu City, Taiwan: Natural Computing Laboratory, Department of Computer Science, National Chiao Tung University. Download.

  4. Chen, Y.-p. (2004). Extending the scalability of linkage learning genetic algorithms: Theory and practice (Technical Report 2004018). Urbana, Illinois, USA: Illinois Genetic Algorithms Laboratory, Department of General Engineering, University of Illinois at Urbana-Champaign. Download.

  5. Llorà, X., Ohnishi, K., Chen, Y.-p., Goldberg, D. E., & Welge, M. E. (2004). Enhanced innovation: A fusion of chance discovery and evolutionary computation to foster creative processes and decision making (Technical Report 2004012). Urbana, Illinois, USA: Illinois Genetic Algorithms Laboratory, Department of General Engineering, University of Illinois at Urbana-Champaign. Download.

  6. Ohnishi, K., Sastry, K., Chen, Y.-p., & Goldberg, D. E. (2004). Inducing sequentiality using grammatical genetic codes (Technical Report 2004007). Urbana, Illinois, USA: Illinois Genetic Algorithms Laboratory, Department of General Engineering, University of Illinois at Urbana-Champaign. Download.

  7. Chen, Y.-p., & Goldberg, D. E. (2004). Introducing subchromosome representations to the linkage learning genetic algorithms (Technical Report 2004001). Urbana, Illinois, USA: Illinois Genetic Algorithms Laboratory, Department of General Engineering, University of Illinois at Urbana-Champaign. Download.

  8. Yu, T.-L., Chen, Y.-p., Goldberg, D. E., & Chen, J.-H. (2003). An adaptive sampling scheme for genetic algorithms on the sampled OneMax problem (Technical Report 2003026). Urbana, Illinois, USA: Illinois Genetic Algorithms Laboratory, Department of General Engineering, University of Illinois at Urbana-Champaign. Download.

  9. Chen, Y.-p., & Goldberg, D. E. (2003). Convergence time for the linkage learning genetic algorithm (Technical Report 2003025). Urbana, Illinois, USA: Illinois Genetic Algorithms Laboratory, Department of General Engineering, University of Illinois at Urbana-Champaign. Download.

  10. Yu, T.-L., Goldberg, D. E., Yassine, A. A., & Chen, Y.-p. (2003). A genetic algorithm design inspired by organizational theory: A pilot study of a dependency structure matrix driven genetic algorithm (Technical Report 2003007). Urbana, Illinois, USA: Illinois Genetic Algorithms Laboratory, Department of General Engineering, University of Illinois at Urbana-Champaign. Download.

  11. Chen, Y.-p., & Goldberg, D. E. (2003a). An analysis of a reordering operator with tournament selection on a GA-hard problem (Technical Report 2003003). Urbana, Illinois, USA: Illinois Genetic Algorithms Laboratory, Department of General Engineering, University of Illinois at Urbana-Champaign. Download.

  12. Chen, Y.-p., & Goldberg, D. E. (2003b). Tightness time for the linkage learning genetic algorithm (Technical Report 2003002). Urbana, Illinois, USA: Illinois Genetic Algorithms Laboratory, Department of General Engineering, University of Illinois at Urbana-Champaign. Download.

  13. Chen, Y.-p., & Goldberg, D. E. (2002). Introducing start expression genes to the linkage learning genetic algorithm (Technical Report 2002007). Urbana, Illinois, USA: Illinois Genetic Algorithms Laboratory, Department of General Engineering, University of Illinois at Urbana-Champaign. Download.

Dissertation and Thesis
  1. Chen, Y.-p. (2004). Extending the scalability of linkage learning genetic algorithms: Theory and practice. Doctoral dissertation, University of Illinois, Urbana, IL, USA.

  2. Chen, Y.-p. (1997). Stochastic sketching: A new method for global optimization. Master's thesis, National Taiwan University, Taipei, Taiwan.
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Updated: September 04, 2008