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Academic Publications

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Journal Papers

  1. Kuo, W.-L., Chang, W.-C., Dai, T.-S., Chen, Y.-p., & Chang, H.-H. (2022). Improving pairs trading strategies using two-stage deep learning methods and analyses of time (in)variant inputs for trading performance. IEEE Access, ‍10, 97030–97046. doi: 10.1109/ACCESS.2022.3204056. (SCI, EI).
  2. Handoyo, S., Chen, Y.-p., Irianto, G., & Widodo, A. (2021). The varying threshold values of logistic regression and linear discriminant for classifying fraudulent firm. Mathematics and Statistics, ‍9(2), 135–143. doi: 10.13189/ms.2021.090207.
  3. Handoyo, S., & Chen, Y.-p. (2020). The developing of fuzzy system for multiple time series forecasting with generated rule bases and optimized consequence part. International Journal of Engineering Trends and Technology, ‍68(12), 118–122. doi: 10.14445/22315381/IJETT-V68I12P220.
  4. Chang, C.-y., & Chen, Y.-p. (2020). AntsOMG: A framework aiming to automate creativity and intelligent behavior with a showcase on cantus firmus composition and style development. Electronics, ‍9(8), 1212. doi: 10.3390/electronics9081212. (SCI). GitHub Repo.
  5. Lin, J.-C., Leu, F.-Y., & Chen, Y.-p. (2016). Impacts of task re-execution policy on MapReduce jobs. The Computer Journal, ‍59(5), 701–714. doi: 10.1093/comjnl/bxv105. (SCI).
  6. Lee, M.-C., Leu, F.-Y., & Chen, Y.-p. (2015). Pareto-based cache replacement for YouTube. World Wide Web, ‍18(6), 1523–1540. doi: 10.1007/s11280-014-0318-9. (SCI, EI).
  7. Lin, J.-C., Leu, F.-Y., & Chen, Y.-p. (2015a). PAReS: A proactive and adaptive redundant system for enhancing MapReduce job completion reliability and service quality. Journal of Information Science and Engineering, ‍31(5), 1775–1793. Download. (SCI).
  8. Lin, J.-C., Leu, F.-Y., & Chen, Y.-p. (2015b). Analyzing job completion reliability and job energy consumption for a heterogeneous MapReduce cluster under different intermediate-data replication policies. Journal of Supercomputing, ‍71(5), 1657–1677. doi: 10.1007/s11227-014-1286-7. (SCI, EI).
  9. Lin, J.-C., Leu, F.-Y., & Chen, Y.-p. (2015c). Impact of MapReduce policies on job completion reliability and job energy consumption. IEEE Transactions on Parallel and Distributed Systems, ‍26(5), 1364–1378. doi: 10.1109/TPDS.2014.2374600. (SCI, EI).
  10. Chen, C.-M., & Chen, Y.-p. (2014a). Connection choice codes. IEICE Transactions on Communications, ‍E97-B(7), 1350–1357. doi: 10.1587/transcom.E97.B.1350. (SCI, EI).
  11. Chen, C.-H., & Chen, Y.-p. (2014b). Quality analysis of discretization methods for estimation of distribution algorithms. IEICE Transactions on Information and Systems, ‍E97-D(5), 1312–1323. doi: 10.1587/transinf.E97.D.1312. (SCI, EI).
  12. Chen, C.-M., Chen, Y.-p., Shen, T.-C., & Zao, J. ‍K. (2013). A practical optimization framework for the degree distribution in LT codes. IEICE Transactions on Communications, ‍E96-B(11), 2807–2815. doi: 10.1587/transcom.E96.B.2807. (SCI, EI).
  13. Lin, J.-C., Leu, F.-Y., & Chen, Y.-p. (2013). Analyzing job completion reliability and job energy consumption for a general MapReduce infrastructure. Journal of High Speed Networks, ‍19(3), 203–214. doi: 10.3233/JHS-130473. (EI).
  14. Lin, J.-Y., & Chen, Y.-p. (2013). Population sizing for inductive linkage identification. International Journal of Systems Science, ‍44(1), 1–13. doi: 10.1080/00207721.2011.577246. (SCI, EI).
  15. Chen, Y.-p., Chuang, C.-Y., & Huang, Y.-W. (2012). Inductive linkage identification on building blocks of different sizes and types. International Journal of Systems Science, ‍43(12), 2202–2213. doi: 10.1080/00207721.2011.566639. (SCI, EI).
  16. Lee, M.-C., Leu, F.-Y., & Chen, Y.-p. (2012). PFRF: An adaptive data replication algorithm based on star-topology data grids. Future Generation Computer Systems, ‍28(7), 1045–1057. doi: 10.1016/j.future.2011.08.015. (SCI, EI).
  17. Chen, C.-H., & Chen, Y.-p. (2011). Convergence time analysis of particle swarm optimization based on particle interaction. Advances in Artificial Intelligence, ‍2011(204750), 1–7. doi: 10.1155/2011/204750.
  18. Lin, J.-Y., & Chen, Y.-p. (2011). Analysis on the collaboration between global search and local search in memetic computation. IEEE Transactions on Evolutionary Computation, ‍15(5), 608–623. doi: 10.1109/TEVC.2011.2150754. (SCI, EI).
  19. Jiang, P., & Chen, Y.-p. (2011). Free lunches on the discrete Lipschitz class. Theoretical Computer Science, ‍412(17), 1614–1628. doi: 10.1016/j.tcs.2010.12.028. (SCI, EI).
  20. Chuang, C.-Y., & Chen, Y.-p. (2010). Sensibility of linkage information and effectiveness of estimated distributions. Evolutionary Computation, ‍18(4), 547–579. doi: 10.1162/EVCO_a_00010. (SCI, EI).
  21. Chen, Y.-p., & Chen, C.-H. (2010). Enabling the extended compact genetic algorithm for real-parameter optimization by using adaptive discretization. Evolutionary Computation, ‍18(2), 199–228. doi: 10.1162/evco.2010.18.2.18202. (SCI).
  22. Chen, Y.-p., & Jiang, P. (2010). Analysis on the facet of particle interaction in particle swarm optimization. Theoretical Computer Science, ‍411(21), 2101–2115. doi: 10.1016/j.tcs.2010.03.003. (SCI, EI).
  23. Chen, Y.-p., & Lin, Y.-y. (2009). Controlling the movement of crowds in computer graphics by using the mechanism of particle swarm optimization. Applied Soft Computing, ‍9(3), 1170–1176. doi: 10.1016/j.asoc.2009.03.004. (SCI, EI).
  24. 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. doi: 10.1109/TSMCB.2007.904019. (SCI, EI).
  25. Chen, Y.-p., & Goldberg, D. ‍E. (2005). Convergence time for the linkage learning genetic algorithm. Evolutionary Computation, ‍13(3), 279–302. doi: 10.1162/1063656054794806. (SCI).
  26. 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, ‍17(1), 47–71. Download. (SCI).
  27. Chen, Y.-p., Horng, J.-T., & Kao, C.-Y. (1999). Stochastic sketching: A new method for global optimization. Soft Computing, ‍3(2), 101–110. doi: 10.1007/s005000050058. (SCI).

Conference and Workshop Papers

  1. Chang, C.-y., & Chen, Y.-p. (2023). Investigating style forming and twisting by adapting AntsOMG for composing second species counterpoint. In Proceedings of 2023 IEEE Congress on Evolutionary Computation (CEC 2023) (pp. 1–8). doi: 10.1109/CEC53210.2023.10253974. (EI). GitHub Repo.
  2. Chang, C.-y., & Chen, Y.-p. (2021a). In the name of creativity: En route to inspiring machines. In Proceedings of 2021 International Conference on Computational Creativity (ICCC’21) (pp. 400–404). GitHub Repo.
  3. Chang, C.-y., & Chen, Y.-p. (2021b). Contrapuntal composition and autonomous style development of organum motets by using AntsOMG. In Proceedings of 2021 IEEE Congress on Evolutionary Computation (CEC 2021) (pp. 2023–2030). doi: 10.1109/CEC45853.2021.9504881. (EI). GitHub Repo.
  4. Lo, F.-Y., Chen, C.-H., & Chen, Y.-p. (2020). Shrinking counterexamples in property-based testing with genetic algorithms. In Proceedings of 2020 IEEE Congress on Evolutionary Computation (CEC 2020) (pp. 1–8). doi: 10.1109/CEC48606.2020.9185807. (EI). GitHub Repo.
  5. Lo, F.-Y., Chen, C.-H., & Chen, Y.-p. (2019). Genetic algorithms as shrinkers in property-based testing. In Proceedings of 2019 ACM SIGEVO Genetic and Evolutionary Computation Conference Companion (GECCO’19 Companion) (pp. 291–292). doi: 10.1145/3319619.3322004. (EI).
  6. Chang, C.-y., & Chen, Y.-p. (2019). Fusing creative operations into evolutionary computation for composition: From a composer’s perspective. In Proceedings of 2019 IEEE Congress on Evolutionary Computation (CEC 2019) (pp. 2113–2120). doi: 10.1109/CEC.2019.8790335. (EI). GitHub Repo.
  7. Huang, S.-Y., & Chen, Y.-p. (2017). Proving theorems by using evolutionary search with human involvement. In Proceedings of 2017 IEEE Congress on Evolutionary Computation (CEC 2017) (pp. 1495–1502). doi: 10.1109/CEC.2017.7969480. (EI). GitHub Repo.
  8. Hsu, W.-L., & Chen, Y.-p. (2016). Learning to select actions in StarCraft with genetic algorithms. In Proceedings of the 2016 Conference on Technologies and Applications of Artificial Intelligence (TAAI 2016) (pp. 270–277). doi: 10.1109/TAAI.2016.7880180. (EI). GitHub Repo.
  9. Yang, L.-A., Liu, J.-P., Chen, C.-H., & Chen, Y.-p. (2016). Automatically proving mathematical theorems with evolutionary algorithms and proof assistants. In Proceedings of 2016 IEEE Congress on Evolutionary Computation (CEC 2016) (pp. 4421–4428). doi: 10.1109/CEC.2016.7744352. (EI). GitHub Repo.
  10. Lee, M.-C., Leu, F.-Y., & Chen, Y.-p. (2015). ReMBF: A reliable multicast brute-force co-allocation scheme for multi-user data grids. In Proceedings of 2015 IEEE 39th Annual Computer Software and Applications Conference (COMPSAC 2015), Volume ‍2 (pp. 774–784). doi: 10.1109/COMPSAC.2015.34. (EI).
  11. Tseng, H.-w., & Chen, Y.-p. (2015). Artistic image processing with cellular automata and evolutionary algorithms. In Proceedings of 2015 IEEE Congress on Evolutionary Computation (CEC 2015) (pp. 2153–2159). doi: 10.1109/CEC.2015.7257150. (EI). GitHub Repo.
  12. Lee, M.-C., Leu, F.-Y., & Chen, Y.-p. (2014). Developing a performance-analysis model for a star-topology data grid from multi-user perspective. In Proceedings of The 6th IEEE International Conference on Intelligent Networking and Collaborative Systems (INCoS 2014) (pp. 242–248). doi: 10.1109/INCoS.2014.83. (EI).
  13. Tsai, P.-C., Chen, C.-M., & Chen, Y.-p. (2014a). A novel evaluation function for LT codes degree distribution optimization. In Proceedings of 2014 IEEE Congress on Evolutionary Computation (CEC 2014) (pp. 3030–3035). doi: 10.1109/CEC.2014.6900609. (EI).
  14. Tsai, P.-C., Chen, C.-M., & Chen, Y.-p. (2014b). PSO-based evacuation simulation framework. In Proceedings of 2014 IEEE Congress on Evolutionary Computation (CEC 2014) (pp. 1944–1950). doi: 10.1109/CEC.2014.6900600. (EI). GitHub Repo.
  15. Lee, M.-C., Leu, F.-Y., & Chen, Y.-p. (2014). Cache replacement algorithms for YouTube. In Proceedings of the 28th IEEE International Conference on Advanced Information Networking and Applications (AINA-2014) (pp. 743–750). doi: 10.1109/AINA.2014.91. (Best paper award, EI).
  16. Lin, J.-C., Leu, F.-Y., Chen, Y.-p., & Munawar, W. (2014). Impact of MapReduce task re-execution policy on job completion reliability and job completion time. In Proceedings of the 28th IEEE International Conference on Advanced Information Networking and Applications (AINA-2014) (pp. 712–718). doi: 10.1109/AINA.2014.87. (EI).
  17. Lee, M.-C., Leu, F.-Y., & Chen, Y.-p. (2013). TSR: Topology reduction from tree to star data grids. In Proceedings of the Seventh International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS-2013) (pp. 678–683). doi: 10.1109/IMIS.2013.122. (EI).
  18. Lin, J.-Y., & Chen, Y.-p. (2013). On the effect of population size and selection mechanism from the viewpoint of collaboration between exploration and exploitation. In Proceedings of 2013 IEEE Workshop on Memetic Computing at Symposium Series on Computational Intelligence (IEEE MC at SSCI 2013) (pp. 16–23). doi: 10.1109/MC.2013.6608202. (EI).
  19. Lin, J.-C., Leu, F.-Y., Lee, M.-C., & Chen, Y.-p. (2013). Deriving job completion reliability and job energy consumption for a general MapReduce infrastructure from single-job perspective. In Proceedings of the 27th IEEE International Conference on Advanced Information Networking and Applications (AINA-2013) (pp. 1642–1647). doi: 10.1109/WAINA.2013.10. (EI).
  20. Tsai, P.-C., Chen, C.-M., & Chen, Y.-p. (2012). Sparse degrees analysis for LT codes optimization. In Proceedings of 2012 IEEE Congress on Evolutionary Computation (CEC 2012) (pp. 2463–2468). doi: 10.1109/CEC.2012.6252861. (EI).
  21. Lin, J.-Y., & Chen, Y.-p. (2012). When and what kind of memetic algorithms perform well. In Proceedings of 2012 IEEE Congress on Evolutionary Computation (CEC 2012) (pp. 2716–2723). doi: 10.1109/CEC.2012.6252894. (EI).
  22. Huang, Y.-w., & Chen, Y.-p. (2010). Detecting general problem structures with inductive linkage identification. In Proceedings of the 2010 Conference on Technologies and Applications of Artificial Intelligence (TAAI 2010) (pp. 508–515). doi: 10.1109/TAAI.2010.86. (EI).
  23. Lin, J.-H., & Chen, Y.-p. (2010). XCS with bit masks. In Proceedings of the 2010 Conference on Technologies and Applications of Artificial Intelligence (TAAI 2010) (pp. 516–523). doi: 10.1109/TAAI.2010.87. (EI).
  24. Chen, Y.-p. (2010). Estimation of distribution algorithms: Basic ideas and future directions. In Proceedings of World Automation Congress 2010 (WAC 2010) (pp. IFMIP–152). Download.
  25. Chen, C.-M., Chen, Y.-p., Shen, T.-C., & Zao, J. (2010a). On the optimization of degree distributions in LT codes with covariance matrix adaptation evolution strategy. In Proceedings of 2010 IEEE Congress on Evolutionary Computation (CEC 2010) (pp. 3531–3538). doi: 10.1109/CEC.2010.5586202. (EI).
  26. Chen, C.-M., Chen, Y.-p., Shen, T.-C., & Zao, J. (2010b). Optimizing degree distributions in LT codes by using the multiobjective evolutionary algorithm based on decomposition. In Proceedings of 2010 IEEE Congress on Evolutionary Computation (CEC 2010) (pp. 3635–3642). doi: 10.1109/CEC.2010.5586340. (EI).
  27. Huang, Y.-W., & Chen, Y.-p. (2009). On the detection of general problem structures by using inductive linkage identification. In Proceedings of ACM SIGEVO Genetic and Evolutionary Computation Conference 2009 (GECCO-2009) (pp. 1853–1854). doi: 10.1145/1569901.1570200. (EI).
  28. Chen, C.-M., Chen, Y.-p., & Zhang, Q. (2009). Enhancing MOEA/D with guided mutation and priority update for multi-objective optimization. In Proceedings of 2009 IEEE Congress on Evolutionary Computation (CEC 2009) (pp. 209–216). doi: 10.1109/CEC.2009.4982950. (EI).
  29. 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. 670–675). Download. (Invited).
  30. 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). doi: 10.1145/1389095.1389169. (EI).
  31. 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). doi: 10.1145/1389095.1389280. (EI).
  32. 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). doi: 10.1109/CEC.2007.4424493. (CPCI-S, EI).
  33. 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). doi: 10.1109/CEC.2007.4424900. (CPCI-S, EI).
  34. 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). doi: 10.1145/1276958.1277096. (EI).
  35. 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). doi: 10.1145/1276958.1277330. (EI).
  36. 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). doi: 10.1145/1276958.1277343. (EI).
  37. 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). doi: 10.1145/1276958.1277357. (EI).
  38. 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). doi: 10.1145/1143997.1144010. (CPCI-S, EI).
  39. 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). doi: 10.1145/1143997.1144174. (CPCI-S, EI).
  40. 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). doi: 10.1145/1143997.1144222. (CPCI-S, EI).
  41. 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). doi: 10.1145/1143997.1144255. (CPCI-S, EI).
  42. 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). doi: 10.1145/1143997.1144301. (CPCI-S, EI).
  43. Chen, Y.-p., & Goldberg, D. ‍E. (2004). Introducing subchromosome representations to the linkage learning genetic algorithms. In Proceedings of Genetic and Evolutionary Computation Conference 2004 (GECCO-2004) (pp. 971–982). (CPCI-S).
  44. Ohnishi, K., Sastry, K., Chen, Y.-p., & Goldberg, D. ‍E. (2004). Inducing sequentiality using grammatical genetic codes. In Proceedings of Genetic and Evolutionary Computation Conference 2004 (GECCO-2004) (pp. 1426–1437). (CPCI-S).
  45. 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. In Proceedings of Genetic and Evolutionary Computation Conference 2004 (GECCO-2004) (pp. 1314–1315). (CPCI-S).
  46. 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). (CPCI-S, EI).
  47. 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).
  48. 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).
  49. Chen, Y.-p., & Goldberg, D. ‍E. (2003a). An analysis of a reordering operator with tournament selection on a GA-hard problem. In Proceedings of Genetic and Evolutionary Computation Conference 2003 (GECCO-2003) (pp. 825–836). (CPCI-S).
  50. Chen, Y.-p., & Goldberg, D. ‍E. (2003b). Tightness time for the linkage learning genetic algorithm. In Proceedings of Genetic and Evolutionary Computation Conference 2003 (GECCO-2003) (pp. 837–849). (CPCI-S).
  51. 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. In Proceedings of Genetic and Evolutionary Computation Conference 2003 (GECCO-2003) (pp. 1620–1621). (CPCI-S).
  52. Chen, Y.-p., & Goldberg, D. ‍E. (2002). Introducing start expression genes to the linkage learning genetic algorithm. In Proceedings of the Seventh International Conference on Parallel Problem Solving from Nature (PPSN VII) (pp. 351–360).
  53. Singh, A., Goldberg, D. ‍E., & Chen, Y.-p. (2002). Modified linkage learning genetic algorithm for difficult non-stationary problems. In Proceedings of Genetic and Evolutionary Computation Conference 2002 (GECCO-2002) (pp. 699).
  54. 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).
  55. Singh, A., Goldberg, D. ‍E., & Chen, Y.-p. (2002). 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).
  56. Yang, J.-M., Chen, Y.-p., Horng, J.-T., & Kao, C.-Y. (1997). Applying family competition to evolution strategies for constrained optimization. In Proceedings of the Sixth International Conference on Evolutionary Programming (EP 97) (pp. 201–211). (EI).
  57. 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).

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. Lin, J.-C., Leu, F.-Y., & Chen, Y.-p. (2015). ReHRS: A hybrid redundant system for improving MapReduce reliability and availability. In Xhafa, F., Barolli, L., Barolli, A., & Papajorgji, P. (Eds.), Modeling and Processing for Next-Generation Big-Data Technologies, Volume ‍4 of Modeling and Optimization in Science and Technologies (pp. 187–209). Springer. doi: 10.1007/978-3-319-09177-8_8. ISBN: 978-3-319-09176-1. Springer Link
  2. Sinha, A., Chen, Y.-p., & Goldberg, D. ‍E. (2005). 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. (Ed.) (2010). Exploitation of linkage learning in evolutionary algorithms, Volume ‍3 of Adaptation, Learning, and Optimization. Springer. ISBN: 978-3-642-12833-2. Springer Link Amazon Link
  2. 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. Yang, L.-A., Liu, J.-P., Chen, C.-H., & Chen, Y.-p. (2016). Automatically proving mathematical theorems with evolutionary algorithms and proof assistants.  ‍(arXiv:1602.07455). Download
  2. Tsai, P.-C., Chen, C.-M., & Chen, Y.-p. (2015). Multiple configurations LT codes.  ‍(arXiv:1510.01823). Download
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
  15. 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: December 13, 2023