Below publications can be also found from the following sources:
Google Scholar; ORCID; Scopus; DBLP; Semantic Scholar.

Edited Books and Special Issues

  1. Preuss, M., Epitropakis, M., Li, X., Fieldsend, J. (Eds.), Metaheuristics for Finding Multiple Solutions, Natural Computing Series, Springer, 2021.
  2. Mitrovic, T., Xue, B., Li, X. (Eds.), The Proceedings of 31st Australasian Joint Conference on Artificial Intelligence (AI’18), Lecture Notes in Artificial Intelligence (LNAI 11320), Wellington, New Zealand, December 11 - 14, 2018.
  3. Shi, Y., Tan, K.C., Zhang, M., Tang, K., Li, X., Zhang, Q., Tan, Y., Middendorf, M., Jin, Y. (Eds.), The Proceedings of the 11th International Conference on Simulated Evolution And Learning (SEAL 2017), Lecture Notes in Computer Science (LNCS 10593), Shenzhen, China, November 10 - 13, 2017, 1041 pages.
  4. Dorigo, M., Birattari, M., Li, X., Lopez-lbanez, M., Ohkura, K., Pinciroli, C., Stutzle, T. (Eds.), "ANTS 2016 special issue: Editorial", Swarm Intelligence, 11:181-183, 2017.
  5. Peng, W., Alahakoon, D., Li, X. (Eds.), The Proceedings of 30th Australasian Joint Conference on Artificial Intelligence (AI'17), Lecture Notes in Artificial Intelligence (LNAI 10400), Melbourne, Australia, August 19 - 20, 2017.
  6. Wagner, M., Li, X. and Hendtlass, T. (Eds.), The Proceedings of Third Australasian Conference on Artificial Life and Computational Intelligence (ACALCI 2017), Lecture Notes in Artificial Intelligence(LNAI 10142), Geelong, Australia, January 31 - February 2, 2017.
  7. Dorigo, M., Birattari, M., Li, X., Lopez-lbanez, M., Ohkura, K., Pinciroli, C., Stutzle, T. (Eds.), The Proceedings of 10th International Conference on Swarm Intelligence (ANTS 2016), Lecture Notes in Computer Science (LNCS 9882), Brussels, Belgium, September 7 - 9, 2016.
  8. Ray, T., Ruhul, S. and Li, X. (Eds.), The Proceedings of Second Australasian Conference on Artificial Life and Computational Intelligence (ACALCI 2016), Lecture Notes in Artificial Intelligence (LNCS 9592), Canberra, Australia, February 2 - 5, 2016.
  9. Fang, W., Li, X., Hu, M. and Zhang, M. (Eds.) (2015). Special Issue of Journal of Applied Mathematics on "Nature-Inspired Algorithms for Real-world Optimization Problems" (accepted 26/08/2015).
  10. Li, X., Tang, K., Suganthan, P.N. and Yang, Z. (Eds.) (2015). Special Issue of Information Sciences Journal (ISJ) on "Nature-Inspired Algorithms for Large Scale Global Optimization", September 2015.
  11. Dick, G., Browne, WN., Whigham, P., Zhang, M., Bui, L.T., Ishibuchi, H., Jin, Y., Li, X., Shi, Y., Singh, P., Tan, KC., Tang, K. (Eds.), The Proceedings of the 10th International Conference on Simulated Evolution And Learning (SEAL 2014), Lecture Notes in Computer Science (LNCS 8886), Dunedin, New Zealand, December 15 - 18, 2014.
  12. Cheung, Y.M., Wang, Y., Liu, H. and Li, X. (2014), Special Issue on "Selected Papers from teh Nith International Conference on Computational Intelligence and Security", The Scientific World Journal, 2014.
  13. Zhang, M., Kirley, M., Li, X.(2011), Special Issue on "Evolutionary Optimization and Learning", Journal of Soft Computing, Vol.15, No.9, 2011.
  14. Kirley, M., Zhang, M. and Li, X. (2009), Special Issue on "Simulated Evolution and Learning", Journal of Evolutionary Intelligence, Vol.2, 2009.
  15. Nicholson, A. and Li, X.(2009), The Proceedings of the 22nd Australasian Joint Conference on Artificial Intelligence (AI 2009), Lecture Notes in Computer Science (LNCS 5866), Melbourne, Australia, December 1 - 4, 2009.
  16. Engelbrecht, A., Li, X., Gambardella, L. and Middendorf, M. (2009), "Special Issue: Swarm Intelligence", IEEE Transactions on Evolutionary Computation, Vol. 13, No.4. August, 2009.
  17. Li, X.; Kirley, M.; Zhang, M.; Green, D.; Ciesielski, V.; Abbass, H.; Michalewicz, Z.; Hendtlass, T.; Deb, K.; Tan, K.C.; Branke, J.; Shi, Y. (Eds.) (2008). The Proceedings of the 7th International Conference on Simulated Evolution And Learning (SEAL 2008), Lecture Notes in Computer Science (LNCS 5361), Melbourne, Australia, December 7 - 10, 2008. 658 pages. ISBN: 978-3-540-89693-7.
  18. Li, X., Luo, W. and Yao, X. (eds.) (2008). Special Issue on "Evolutionary Optimization", Journal of Computer Science Technology, Vol.23, No.1, January 2008.
  19. Li, X., Luo, W. and Yao, X. (eds.) (2008). Special Issue on "Simulated Evolution and Learning", International Journalof Computational Intelligence and Applications (IJCIA), World Scientific Press, Vol.7, No.2, June 2008.
  20. Li, X., Luo, W. and Yao, X. (eds.) (2008). Special Issue on "Theoretical Foundations of Evolutionary Computation", Journal of Genetic Programming and Evolvable Machines, Springer, Vol.9, No.2, June 2008.
  21. Li, X., Luo, W. and Yao, X. (eds.) (2007). Special Issue on "Evolutionary Learning and Optimization",Connection Science, Volume 19, Issue 4, December 2007, Taylor & Francis, London, UK.
  22. Wang, T.-D., Li, X., Chen, S.-H., Wang, X., Abbass, H., Iba, H, Chen, G. and Yao, X. (eds.) (2006). The Proceedings of the 6th International Conference on Simulated Evolution And Learning (SEAL 2006), Lecture Notes in Computer Science (LNCS 4247), Hefei, China, October 15-18, 2006. 940 pages. ISBN: 3-540-47331-9.

Book Chapters

  1. Preuss, M., Epitropakis, M., Li, X., Fieldsend, J. "Multimodal Optimization: Formulation, Heuristics, and a Decade of Advances", in Metaheuristics for Finding Multiple Solutions, pp.1 - 26, Springer, 2021.
  2. Miessen, A., Najman, J. and Li, X., "Finding Representative Solutions in Multimodal Optimization for Enhanced Decision-Making", in Metaheuristics for Finding Multiple Solutions, pp.57 - 88, Springer, 2021.
  3. Li, X. and Clerc, M., "Swarm Intelligence", in Handbook of Metaheuristics (3rd edition), Gendreau, Michel, Potvin, Jean-Yves (Eds.), International Series in Operations Research & Management Science, vol.272, Springer, Cham, pp.353 - 384, 2018.
  4. Li, X., "Multimodal Optimization using Niching Methods", in Wiley Encyclopedia of Electrical and Electronics Engineering, Wiley, pp.1 - 8 (Published Online: 16/11/2016).
  5. Carrese, R. and Li, X., (2015), "Preference-Based Multiobjective Particle Swarm Optimization for Airfoil Design", in Kacprzyk and Pedrycz (editors), Springer Handbook of Computational Intelligence, Springer, 2015, pp.1311-1331.
  6. Li, X. (2011), "Developing Niching Algorithms in Particle Swarm Optimization", Handbook of Swarm Intelligence - Concepts, Principles and Applications, Series on Adaptation, Learning, and Optimization, Vol. 8, B.K. Panigrahi, Y.Shi, and M.-H. Lim (eds.), Springer, 2011, pp.67-88.
  7. Bird, S. and Li, X., (2010), "Improving Local Convergence in Particle Swarms by Fitness Approximation Using Regression", in Computational Intelligence in Expensive Optimization Problems (Evolutionary Learning and Optimization, book series), Vol. 2, Y. Tenne and C.-K. Goh (eds.), Springer, 2010, pp.265 - 293.
  8. Blum, C. and Li, X. (2008). "Swarm Intelligence in Optimization", in Blum, C. and Merkle, D. (editors), Swarm Intelligence - Introduction and Applications, Springer, 2008, pp.43 - 85.
  9. Blackwell, T., Branke, J. and Li, X. (2008). "Particle Swarms for Dynamic Optimization Problems", in Blum, C. and Merkle, D. (editors), Swarm Intelligence - Introduction and Applications, Springer, 2008, pp.193 - 217.
  10. Li, X. and Sutherland, S. (2004). "A Real-Coded Cellular Genetic Algorithm Inspired by Predator-Prey Interactions". In Kay Chen Tan, Meng Hiot Lim, Xin Yao, andLipo Wang, editors, Recent Advances in Simulated Evolution and Learning, Advances in Natural Computation. World Scientific 2004, pp.191 - 207.
  11. Li, X. and Magill, W. (2000), "Modelling Fire Behaviours under Environmental Influences Using a Cellular Automaton Approach",Applied Complexity - from Neural Nets to Managed Landscape, edited by Halloy,S. and Williams, T., p.164-178.

Journals

  1. Thiruvady, D., Nguyen, S., Sun, Y., Shiri, F., Zaidi, N, Li, X. (2024), "Adaptive Population-based Simulated Annealing for Resource Constrained Job Scheduling with Uncertainty", Intenational Journal of Production Research (accepted on 11/01/2024).
  2. Liu, Y., Zuo, X., Li, X., and Nie, S. (2023), "A Genetic Algorithm with Trip-adjustment Strategy for Multi-depot Electric Bus Scheduling Problems", Engineering Optimization (published online: 28/07/2023).
  3. Chu, R., Chik, L., Chan, J., Gutzman, K., Li, X. (2023), "Automatic Meter Error Detection with a Data-Driven Approach", Engineering Applications of Artificial Intelligence, Vol.123, Part C, 2023, 106466.
  4. Weiner, J., Ernst, A.E., Li, X., and Sun, Y. (2023), "Ranking Constraint Relaxations for Mixed Integer Programs using a Machine Learning Approach"", EURO Journal on Computational Optimization, Volume 11, 2023, 100061.
  5. Shen, Y., Eberhard, A., Sun, Y., Li, X., Ernst A.T. (2023), "Adaptive Solution Prediction for Combinatorial Optimization", European Journal of Operational Research, 309(3): 1392-1408, September 2023.
  6. Ma, X., Tao, H., Li, X., Qi, Y., Wang, L., and Zhu, Z. (2023), "Multi-objectivization of Single-objective Optimization in Evolutionary Computation: a Survey", IEEE Transactions on Cybernetics, 53(6): 3702-3715, June 2023.
  7. Sun, Y., Esler, S., Thiruvady, D., Ernst, A.T., Li, X., and Morgan, K. (2022), "Instance Space Analysis for the Car Sequencing Problem", Annals of Operations Research (accepted on 24/06/2022).
  8. Sun, Y. Wang, S., Shen, Y., Li, X., Ernst, A.T., and Kirley, M. (2022), "Boosting Ant Colony Optimization via Solution Prediction and Machine Learning", Computers and Operations Research, Vol.143, July 2022, 105769.
  9. Ma, X., Huang, Z., Li, X., Wang, L., Qi, Y. and Zhu, Z. (2022), "Merged Differential Grouping for Large-scale Global Optimization", IEEE Transactions on Evolutionary Computation, 26(6):1439-1451, December 2022.
  10. Thiruvady, D., Nguyen, S., Shiri, F., Zaidi, N., and Li, X. (2022), "Surrogate-assisted Population Based ACO for Resource Constrained Job Scheduling with Uncertainty", Swarm and Evolutionary Computation, Vol.69, March 2022, 101029.
  11. Wan, X., Zuo X., Li, X. and Zhao, X. (2022), "A Hybrid Multiobjective GRASP for a Multi-row Facility Layout Problem with Extra Clerances", International Journal of Production Research, 60(3):957-976, 2022.
  12. Omidvar, N., Li, X., and Yao, X. (2022), "A Review of Population-based Metaheuristics for Large-scale Black-box Global Optimization: Part I", IEEE Transactions on Evolutionary Computation, 26(5): 802-822, October 2022.
  13. Omidvar, N., Li, X., and Yao, X. (2022), "A Review of Population-based Metaheuristics for Large-scale Black-box Global Optimization: Part II", IEEE Transactions on Evolutionary Computation, 26(5): 823-843, October 2022.
  14. Islam, J., Li, X., and Deb, K. (2022), "A Speciation-based Bilevel Niching Method for Multimodal Truss Design Problems", Journal of Combinatorial Optimization, 44:172-206, 2022.
  15. Ma, X.,Zheng, Y.,Zhu,Z., Li, X., Wang, L., Qi,Y. Yang, J. (2021), "Improving Evolutionary Multitasking Optimization by Leveraging Inter-Task Gene Similarity and Mirror Transformation", IEEE Computational Intelligence Magazine, 16(4):38 - 53.
  16. Liu, D., Qi, Y., Yang, R., Quan Y., Li, X., Miao, Q. (2021), "A Tri-objective Preference-based Uniform Weight Design Method using Delaunay Triangulation", Soft Computing, 25:9703 - 9729.
  17. Weiner, J., Ernst, A.T., Li, X., Sun, Y. and Deb, K. (2021), "Solving the Maximum Edge Disjoint Path Problem Using a Modified Lagrangian Particle Swarm Optimisation Hybrid", European Journal of Operational Research, 293(3):847-862, September 2021.
  18. Ma, X., Yin, J., Zhu, A., Li, X., Yu, Y., Wang, L., Qi, Y. and Zhu, Z. (2021), "Enhanced Multifactorial Evolutionary Algorithm with Meme Helper-tasks", IEEE Transactions on Cybernetics, 52(8):7837 - 7851.
  19. Sun, Y., Li, X., Ernst, A. (2021), "Using Statistical Measures and Machine Learning for Graph Reduction to Solve Maximum Weight Clique Problems", IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(5): 1746 -1760, May 2021 (Source codes).
  20. Sun, Y., Ernst, A.T., Li, X. and Weiner, J. (2021), "Generalization of Machine Learning for Problem Reduction: a Case Study on Travelling Salesman Problems", OR Spectrum, 43:607-633, 2021 Source codes).
  21. Ma, X., Yu, Y., Li, X., Qi, Y., Zhu, Z. (2020),"A Survey of Weight Vector Adjustment Methods for Decomposition Based Multi-objective Evolutionary Algorithms", IEEE Transactions on Evolutionary Computation, 24(4):634-649, August 2020.
  22. Ghasemishabankareh, B, Ozlen, M., Li, X., Neumann, F. (2020), "Probabilistic Tree-Based Representation for Solving Minimum Cost Integer Flow Problems with Nonlinear Non-convex Cost Functions", Applied Softcomputing, Vol.86, 2020, 105951.
  23. Zambetta, F., Raffe, W., Tamassia, M., Mueller, F., Li, X., Quinten, N., Patibanda, R., Deng, D. and Satterley, J. (2020), "Reducing Perceived Waiting Time in Theme Park Queues via an Augmented Reality Game", ACM Transactions on Computer-Human Interaction, Vol.27, No.1, Article 3, January 2020.
  24. Qi, Y., Liu, D., Li, X., Lie, J., Xu, X. and Miao, Q. (2020), "An adaptive penalty-based boundary intersection method for many-objective optimization problem", Information Sciences, 509: 356 - 375, January 2020.
  25. Ghasemishabankareh, B, Ozlen, M., Li, X., and Deb, K. (2020),"A Genetic Algorithm with Local Search for Solving Single-Source Single-Sink Nonlinear Non-Convex Minimum Cost Flow Problems", Soft Computing, 24: 1153-1169.
  26. Yue, C., Qu, B.,Yu, K., Liang, L. and Li, X. (2019), "A novel scalable test problem suite for multimodal multiobjective optimization", Swarm and Evolutionary Computation, 48: 62 - 71, August 2019.
  27. Li, N., Yang, L., Li, X., Li, X., Tu, J. and Cheung, C.P. (2019), "Multi-objective optimization for designing of high-speed train cabin ventilation system using particle swarm optimization and multi-fidelity Kriging", Building and Environment, 155: 161 - 174, May 2019.
  28. Turabieh, H., Mafarja, M. and Li, X. (2019), "Iterated Feature Selection Algorithms with layered Recurrent Neural Network for Software Fault Prediction", Expert Systems with Applications, 122: 27 - 42, May 2019.
  29. Kazimipour, B., Omidvar, N., Qin, A.K., Li, X., Yao, X. (2019), "Bandit-Based Cooperative Coevolution for Tackling Contribution Imbalance in Large-Scale Optimization Problems", Applied Softcomputing, 76: 265 - 281, March 2019.
  30. Qi, Y., Li, X., Yu, J. and Miao, Q. (2019), "User-preference based decomposition in MOEA/D without using an ideal point", Swarm and Evolutionary Computation, 44:597 - 611, February 2019.
  31. Ma, X. Li, X., Zhang, Q., Tang, K., Liang Z., Xie, W., Zhu, Z. (2019),"A Survey on Cooperative Co-evolutionary Algorithms", IEEE Transactions on Evolutionary Computation, 23(3): 421 - 441, June 2019.
  32. Mafarja, M., Aljarah, I. Heidari, A.A., Faris, H., Fournier-Viger, P., Li, X. and Mirjalili, S. (2018), "Binary Dragonfly Optimization for Feature Selection using Time-Varying Transfer functions", Knowledge-Based Systems, 161:185 - 204, December, 2018.
  33. Liu, H., Wang, Y., Liu, L. and Li, X. (2018), "A two phase hybrid algorithm with a new decomposition method for large scale optimization", Integrated Computer Aided Engineering, 25(4):349 - 367, September 2018.
  34. Tamassia, M., Zambetta, F., Raffe, W.L., Mueller, F.F., and Li, X. (2018), "Learning Options from Demonstrations: A Pac-Man Case Study", IEEE Transactions on Games, 10(1): 91 - 96, March 2018.
  35. Xie, J., Mei, Y., Ernst, A.T., Li, X., and Song, A. (2018),"A Bi-level Optimization Model for Grouping Constrained Storage Location Assignment Problems", IEEE Transactions on Cybernetics, 48(1): 385 - 398, January 2018.
  36. Zhang, A., Sun, G., Ren, J., Li, X., and Wang, Z., Jia, X. (2018), "A Dynamic Neighborhood Learning-Based Gravitational Search Algorithm", IEEE Transactions on Cybernetics, 48(1): 436 - 447, January 2018.
  37. Qi, Y., Yu, J., Li, X., Quan, Y., Miao, Q. (2018),"Enhancing Robustness of the Inverted PBI Scalarizing Method in MOEA/D". Applied Soft Computing, 71:1117 - 1132, October 2018.
  38. Wang, Y., Liu, H., Wei, F., Zong, T. and Li, X. (2018), "Cooperative Co-evolution with Formula-based Variable Grouping for Large-Scale Global Optimization", Evolutionary Computation Journal, MIT Press, 26(4): 569 - 596, 2018.
  39. Lin, J. Wang, Z.J., Li, X., (2017), "A backtracking search hyper-heuristic for the distributed assembly flow-shop scheduling problem", Swarm and Evolutionary Computation, 36:124 - 135, October 2017.
  40. Islam, M.J., Li, X., Mei, Y., (2017), "A Time-Varying Transfer Function for Balancing Exploration and Exploitation ability of a Binary PSO", Applied Softcomputing, 59:182 - 196.
  41. Omidvar, M., Yang, M., Mei, Y., Li, X., and Yao, X. (2017),"DG2: A Faster and More Accurate Differential Grouping for Large-Scale Black-Box Optimization", IEEE Transactions on Evolutionary Computation, 21(6): 929 - 942, December 2017 (DG2 source codes in C++/Matlab).
  42. Li, N., Cheung, S., Li, X. and Tu, J. (2017), "Multi-objective optimization of HVAC system using NSPSO and Kriging algorithms - A case study", Building Simulation, 10(5): 769 - 781, October 2017.
  43. Li, X., Epitropakis, M.G., Deb, K., and Engelbrecht, A. (2017), "Seeking Multiple Solutions: an Updated Survey on Niching Methods and Their Applications", IEEE Transactions on Evolutionary Computation, 21(4):518 - 538, August 2017 (Download a local copy).
  44. Qi, Y., Yu, J., Li, X., Wei, Y., and Miao, Q. (2017), "Reservoir Flood Control Operation Using Multi-objective Evolutionary Algorithm with Decomposition and Preferences", Applied Soft Computing, 50:21 - 33, January 2017.
  45. Zheng, J., Yu, G., Zhu, Q., Li, X., and Zou, J. (2017),"On decomposition methods in interactive user-preference based optimization", Applied Soft Computing, 52:952 - 973, March 2017.
  46. Yang, M., Omidvar, M., Li, C., Li, X., Cai, Z., Kazimipour, B. and Yao, X. (2017),"Efficient Resource Allocation in Cooperative Co-evolution for Large-Scale Global Optimization", IEEE Transactions on Evolutionary Computation, 21(4):493 - 505, August 2017.
  47. Tang, K., Wang, J., Li, X., Yao, X., (2017), "A Scalable Approach to Capacitated Arc Routing Problems based on Hierarchical Decomposition", IEEE Transactions on Cybernetics, 47(11): 3928 - 3940, November, 2017.
  48. Sun, G., Zhang, A., Jia, X., Li, X., Ji, S., and Wang, Z. (2016),"DMMOGSA: Diversity-enhanced and memory-based multi-objective gravitational search algorithm", Information Sciences, 363:52 - 71, October 2016.
  49. Lee, G., Zambetta, F., Li, X., Paolini, A., (2016), "Utilising Reinforcement Learning to Develop Strategies for Driving Auditory Neural Implants", Journal of Neural Engineering 13(4):046027, 2016.
  50. Ghasemishabankareh, B., Li, X., Ozlen, M., (2016), "Cooperative coevolutionary differential evolution with improved augmented Lagrangian to solve constrained optimisation problems", Information Sciences, Volume 369, pp.441-456, 2016.
  51. Qi, Y., Bao, L., Ma, X., Miao, Q., Li, X. (2016), "Self-adaptive Multi-objective Evolutionary Algorithm based on Decomposition for Large-scale problems: A Case Study on Reservoir Flood Control Operation", Information Sciences, Volume 367 - 368, pp.529-549, 2016.
  52. Mei, Y., Salim, F. and Li, X. (2016), "Efficient Meta-heuristics for the Multi-Objective Time-Dependent Orienteering Problem", European Journal of Operational Research, Volume 254, pp.443-457, 2016.
  53. Liu, J., Mei, Y. and Li, X. (2016), "An Analysis of the Inertia Weight Parameter for Binary Particle Swarm Optimization", IEEE Transactions on Evolutionary Computation, 20(5): 666-681, October 2016.
  54. Mei, Y., Li, X., and Yao, X. (2016), "On Investigation of Interdependence Between Sub-problems of the Travelling Thief Problem ", in Softcomputing, Springer, 20(1): 157--172, January 2016.
  55. Amini, I., Sanderson, M., Martinez, D. and Li, X. (2016), "Improving Patient Record Search: A Meta-data based Approach", Information Processing & Management, Elsevier, United Kingdom, vol. 52, no. 2, pp.258-272, 2016.
  56. Mei, Y., Omidvar, M., Li, X. and Yao, X. (2016), "A Competitive Divide-and-Conquer Algorithm for Unconstrained Large Scale Black-Box Optimization", ACM Transactions on Mathematical Software (TOMS), 42(2), Article 13, 24 pages, June 2016.
  57. Qi, Y., Hou, Z. Li, H., Huang, J. and Li, X. (2015), "A Decomposition Based Memetic Algorithm for Multi-objective Vehicle Routing Problem with Time Windows", Computers & Operations Research, 62: 61 - 67, 2015.
  58. Omidvar, M., Li, X. and Tang, K. (2015), "Designing Benchmark Problems for Large-Scale Continuous Optimization", Information Sciences, Volume 316, pp.419-436.
  59. Raffe, W., Zambetta, F., Li, X. and Stanley, K. (2015), "An Integrated Approach to Personalized Procedural Map Generation using Evolutionary Algorithms", IEEE Transactions on Computational Intelligence and AI in Games, 7(2):139-155, June 2015.
  60. Bonyadi, M.R., Michalewicz, Z. and Li, X. (2014), "An Analysis of the Velocity Updating Rule of the Particle Swarm Optimization Algorithm", Journal of Heuristics, 20(4):417 - 452, August 2014.
  61. Mei, Y.,Li, X. and Yao, X. (2014), "Cooperative Co-evolution with Route Distance Grouping for Large-Scale Capacitated Arc Routing Problems", IEEE Transactions on Evolutionary Computation, 18(3): 435-449, June 2014 (source code in C).
  62. Omidvar, M.,Li, X. Mei, Y. Yao, X. (2014), "Cooperative Co-evolution with Differential Grouping for Large Scale Optimization", IEEE Transactions on Evolutionary Computation, 18(3): 378-393, June 2014 (DG source code in Matlab,DG with CC framework, DECC-D, DECC-DML)(2017 IEEE CIS "IEEE Transactions on Evolutionary Computation Outstanding Paper Award").
  63. Jiang, B. Wang, N. and Li, X. (2013), "Particle Swarm Optimizer with Ageing Operator for Multimodal Function Optimization", International Journal of Computational Intelligence Systems, 6(5): 826-880.
  64. Donate, J.P., Li, X. Gutierrez, G. and Sanchis, A. (2013), "Time series forecasting by evolving artificial neural networks with genetic algorithms, differential evolution and estimation of distribution algorithm", Journal of Neural Computing & Applications, Springer, 22:11-20.
  65. Carrese, R., Winarto, H., Li, X., Sobester, A. and Ebenezer, S. (2012), "A Comprehensive Preference-based Optimization Framework with Application to High-lift Aerodynamic Design". Engineering Optimization, Taylor & Francis, 44(10): 1209-1227.
  66. Li, X. and Yao, X. (2012), "Cooperatively Coevolving Particle Swarms for Large Scale Optimization,'' IEEE Transactions on Evolutionary Computation, 16(2): 210-224, April 2012(source code).
  67. Bonyadi, M. R. and Li, X. (2012), "A New Discrete Electromagnetism-based Meta-heuristic for Solving the Multidimensional Knapsack Problem Using Genetic Operators", Operational Research, 12(2): 229-252, August 2012 (view PDF).
  68. Carrese, R., Sobester, A., Winarto, H., and Li, X. (2011), "Swarm heuristic for identifying preferred solutions in surrogate-based multiobjective engineering design", American Institute of Aeronautics and Astronautics Journal, 49(7): 1437- 1449, July 2011.
  69. Iorio, A. and Li, X. (2011), "Improving the performance and scalability of Differential Evolution on problems exhibiting parameter interactions", special issue on "Evolutionary Optimisation and Learning", Journal of Soft Computing, 15(9): 1769-1792.
  70. Ronkkonen, J., Li, X., Kyrki, V. and Lampinen, J. (2011), "A framework for generating tunable test functions for multimodal optimization", special issue on "Evolutionary Optimisation and Learning", Journal of Soft Computing, 15(9): 1689-1706.
  71. Zhang, M., Kirley, M., Li, X.(2011), Guest editorial: "Evolutionary Optimization and Learning", Journal of Soft Computing, 15(9): 1671 -1673.
  72. Li, X. (2010), "Niching without Niching Parameters: Particle Swarm Optimization Using a Ring Topology", IEEE Transactions on Evolutionary Computation, 14 (1): 150-169,February 2010 (PDF is available here, and source code).
  73. Kirley, M., Zhang, M. and Li, X.(2009), Guest editorial: "Special Issue on Simulated Evolution and Learning", Journal of Evolutionary Intelligence, 2:149 - 150.
  74. Engelbrecht, A., Li, X., Gambardella, L. and Middendorf, M. (2009), Guest editorial: "Special Issue: Swarm Intelligence", IEEE Transactions on Evolutionary Computation, 13(13): 676-677, August 2009.
  75. Khan, A. A., Bashir, S., Naeem, M.,Shah, S.I. and Li, X. (2008), "Symbol Detection in Spatial Multiplexing System Using Particle Swarm Optimization Meta-heuristics", International Journal of Communication Systems, 21(12): 1239-1257, Wiley, December 2008.
  76. Li, X., Luo, W. and Yao, X. (eds.) (2008), Guest editorial: "Special Issue on Evolutionary Optimization", Journal of Computer Science Technology, 23(1):1, January 2008.
  77. Li, X., Luo, W. and Yao, X. (eds.) (2008), Guest editorial: "Special Issue on Simulated Evolution and Learning", International Journalof Computational Intelligence and Applications (IJCIA), World Scientific Press, 7(2): 1, June 2008.
  78. Li, X., Luo, W. and Yao, X. (eds.) (2008), Guest editorial: "Special Issue on Theoretical Foundations of Evolutionary Computation", Journal of Genetic Programming and Evolvable Machines, Springer,9(2): 107 - 108, June 2008.
  79. Li, X., Luo, W. and Yao, X. (eds.) (2007), Guest editorial:"Special Issue on Evolutionary Learning and Optimization",Connection Science,19(4): 279-280, December 2007, Taylor & Francis, London, UK.
  80. Iorio, A. and Li, X. (2008), "Rotated Problems and Rotationally Invariant Crossover in Evolutionary Multi-Objective Optimization". International Journal of Computational Intelligence and Applications (IJCIA),Special issue on "Simulated Evolution and Learning", World Scientific Press, 7(2): 149 - 186, June 2008 (draft copy).
  81. Li, L., Zhou, J., Yu, X., and Li, X. (2007),"Constrained Power Plants Unit Loading Optimization using Particle Swarm Optimization Algorithm", WSEAS Transactions on Information Science and Applications,4(2): 296-302, February 2007.
  82. Parrott, D. and Li, X. (2006), "Locating and Tracking Multiple Dynamic Optima by a Particle Swarm Model Using Speciation", IEEE Transactions on Evolutionary Computation, 10(4):440-458, August 2006.
  83. Gamble, T. and Li, X. (2003),"Emergence of Cooperation in the IPD Game using Spatial Interactions", International Journal of Knowledge-Based Intelligent Engineering Systems, 7(3): 124-131, Special issue on Evolutionary Computing.
  84. Li, X. and Magill, W., (2003), "Critical Densityin a Fire Spread Model under Environmental Influence", International Journalof Computational Intelligence and Applications (IJCIA), 3(2): 145-155, Special issue on "Artificial Life", World Scientific Press(view PDF).
  85. Li, X. (2002), "Connectionist learning: Acomparison of neural networks and an optical thin-film multilayer model", Connection Science, 14(1): 49 - 63, March 2002, Taylor & Francis, London, UK.
  86. Li, X. and Magill, W. (2000), "Modelling FireBehaviours under Environmental Influences Using a Cellular Automaton Approach", ComplexityInternational, vol. 8.
  87. Li, X. and Purvis, M.K.(1999), "Pattern Recognitionby an Optical Thin-Film Multilayer Learning Model", Annals of Mathematicsand Artificial Intelligence,26: 1-4, p.193-213, Baltzer Science Publishers, Netherlands. (view PDF).

Refereed Conferences

  1. Taylor, K., Ha, H., Li, M., Li, X. and Chan, J. (2024), "Accelerated Bayesian Preference Learning for Efficient Evolutionary Multi-objective Optimisation", in Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion} (GECCO), Melbourne, Australia, ACM, pp.371 - 374.
  2. Blair, A., Khodadadian, A., Li, X., Bab-Hadiashar, A., and Hoseinnezhad, R. (2024), "Evaluation of Genetic Algorithms in Multi-Vehicle Control for Multi-Target Tracking Applications", in Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion} (GECCO), Melbourne, Australia, ACM, pp.631 - 634.
  3. Xu, H., Shen, Y., Sun, Y. and Li, X. (2024), "Machine Learning-Enhanced Ant Colony Optimization for Column Generation", in Proceedings of the 2024 Genetic and Evolutionary Computation Conference} (GECCO), Melbourne, Australia, ACM, pp.1073 - 1081.
  4. Ahrari, A., Fieldsend, J., Preuss, M., Li, X. and Epitropakis, M. (2024), "New Tunable Test Problems for Benchmarking Niching Methods for Multimodal Optimization", in Proceedings of the 2024 Genetic and Evolutionary Computation Conference} (GECCO), Melbourne, Australia, ACM, pp.4 - 12.
  5. Yazdani, D, Branke, J., Khorshidi, M.S., Omidvar, M.N., Li, X., Gandomi, A.H., and Yao, X. (2024), "Clustering in Dynamic Environments: A Framework for Benchmark Dataset Generation With Heterogeneous Changes", in Proceedings of the 2024 Genetic and Evolutionary Computation Conference} (GECCO), Melbourne, Australia, ACM, pp.50 - 58.
  6. Ghasemishabankareh, B., Li, X. and Ozlen, M. (2024), "User-Preference Based Evolutionary Algorithms for Solving Multi-Objective Nonlinear Minimum Cost Flow Problems", in Proceedings of the 2024 Genetic and Evolutionary Computation Conference} (GECCO) , Melbourne, Australia, ACM, pp.502 - 510.
  7. Komarnicki, M.M., Przewozniczek, M.W., Tinos, R. and Li, X. (2024), "Overlapping Cooperative Co-Evolution for Overlapping Large-Scale Global Optimization Problems", in Proceedings of the 2024 Genetic and Evolutionary Computation Conference (GECCO), Melbourne, Australia, ACM, pp.665 - 673.
  8. Shen, Y., Sun, Y., Li, X., Cao, Z., Eberhard, A. and Zhang, G. (2024), "Adaptive Stabilization Based on Machine Learning for Column Generation", Forty-first International Conference on Machine Learning (ICML 2024) (accepted on 02/05/2024).
  9. Nguyen, M.H., Huynh, P.D., Dau, S.H. and Li, X. (2023), "Rug-pull Malicious Token Detection on Blockchain Using Supervised Learning with Feature Engineering", in Proceedings of the 2023 Australasian Computer Science Week, pp.72 - 81.
  10. Kenny, A., Ray, T., Singh, H.K. and Li, X. (2023), "A Test Suite for Multi-objective Multi-fidelity Optimization", in Proceedings of International Conference on Evolutionary Multi-Criterion Optimization (EMO 2023), pp.361 - 373.
  11. Sun, Y., Ernst, A., Li, X., Weiner, J. (2023), "Learning to Generate Columns with Application to Vertex Coloring", Proceedings of the Eleventh International Confernece on Learning Representations (ICLR 2023) (accepted on 22/01/2023).
  12. Blair, A., Gostar, A.K., Tennakoon, R., Bab-Hadiashar, A. Li, X., Palmer, J. and Hoseinnezhad, R. (2022), "Distributed Multi-Sensor Control for Multi-Target Tracking", in Proceedings of 2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS), pp.231 - 239.
  13. Assimi, H., Newmann, F., Wagner, M. and Li, X. (2022), "Novelty-Driven Binary Particle Swarm Optimisation for Truss Optimisation Problems", Proceedings of European Conference on Evolutionary Computation in Combinatorial Optimization (EvoCOP'2022), part of EvoStar'2022, pp.111-126.
  14. Shen, Y., Sun, Y., Eberhard, A. and Li, X., and Ernst, A. (2022), "Enhancing Column Generation by a Machine-Learning-Based Pricing Heuristic for Graph Coloring", Proceedings of Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22), pp.9926 - 9934.
  15. Shen, Y., Sun, Y., Eberhard, A. and Li, X. (2021) "Learning Primal Heuristics for Mixed Integer Programs", in Proceedings of 2021 International Joint Conference on Neural Networks (IJCNN), IEEE. (accepted on 11/04/2021)
  16. Taylor, K., Ha, H., Li, M., Chan, J. and Li, X. (2021), "Bayesian Preference Learning for Interactive Multi-objective Optimisation", in Proceedings of the 2021 Conference on Genetic and Evolutionary Computation Conference (GECCO), Lille, France, ACM, pp.466-475.
  17. Weiner, J., Li, X., Ernst. A., Sun, Y. (2020), "Automatic Decomposition of Integer Programs for Lagrangian Relaxation Using a Multiobjective Approach", in Proceedings of the 2020 Conference on Genetic and Evolutionary Computation Conference (GECCO), Cancun, Mexico, ACM,pp.263 - 270 (nominated for a best paper award).
  18. Haqqani, M., Li, X., Yu, X. (2020), "Non-deterministic Journey Planning in Multi-modal Transportation Networks: a Meta-heuristic Approach", Proceedings of the 2020 Conference on Genetic and Evolutionary Computation Conference (GECCO), Cancun, Mexico, ACM, pp.1098 - 1106.
  19. Sun, Y., Wang, W., Kirley, M., Li, X., Chan, J. (2020), "Revisiting Probability Distribution Assumptions for Information Theoretic Feature Selection", Proceedings of Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), 34(04), pp.5908 - 5915.
  20. Kenny, A., Li, X., Ernst, A.T. and Sun, Y., (2019), "An Improved Merge Search Algorithm For the Constrained Pit Problem in Open-pit Mining", in Proceedings of the 2019 Conference on Genetic and Evolutionary Computation Conference (GECCO), Prague, Czech Republic, ACM, pp.294 - 302, 2019.
  21. Sun,Y., Li, X., Ernst, A. and Omidvar, N. (2019), "Decomposition for Large-scale Optimization Problems with Overlapping Components", in Proceedings of Congress of Evolutionary Computation (CEC 2019), IEEE, pp.318 - 325, 2019 (Winner of IEEE CEC'2019 Large-Scale Global Optimization (LSGO) competition) (Draft version).
  22. Taylor, K., Li, X. and Chan, J. (2019), "Improving Algorithm Response to Preference Changes in Multiobjective Optimisation Using Archives", in Proceedings of Congress of Evolutionary Computation (CEC 2019), IEEE, pp.2442 - 2449, 2019.
  23. Ghasemishabankareh, B., Ozlen, M. and Li, X. (2019),"NSGA-II for Solving Multiobjective integer Minimum Cost Flow Problem with Probabilistic Tree-based Representation", Proceedings of the 10th International Confernece on Evolutionary Multi-Criterion Optimization (EMO 2019), pp.541 - 552, 2019.
  24. Haqqani, M., Ashrafzadeh, A., Yu, X. and Li, X. (2018), "Conditional Preference Learning for Personalized and Context-Aware Journey Planning", in Proceedings of the 15th International Conference on Parallel Problem Solving from Nature (PPSN'2018), LNCS, Springer, Coimbra, Portugal, pp.451 - 463, 2018.
  25. Ghasemishabankareh, B., Ozlen, M., Neumann, F. and Li, X. (2018), "A Probabilistic Tree-Based Representation for Non-convex Minimum Cost Flow Problems", in Proceedings of the 15th International Conference on Parallel Problem Solving from Nature (PPSN'2018), LNCS, Springer, Coimbra, Portugal, pp.69 - 81, 2018.
  26. Taylor, K. and Li, X. (2018), "Interactive Multiobjective Optimisation: Preference Changes and Algorithm Responsiveness", in Proceedings of the 2018 Conference on Genetic and Evolutionary Computation Conference (GECCO), Kyoto, Japan, ACM, pp.761-768, 2018.
  27. Sun, Y., Kirley, M. and Li, X. (2018), "Cooperative Co-evolution with Online Optimizer Selection for Large-Scale Optimization", in Proceedings of the 2018 Conference on Genetic and Evolutionary Computation Conference (GECCO), Kyoto, Japan, ACM, pp.1079-1086, 2018.
  28. Sun, Y., Kirley, M. and Li, X. (2018), "Adaptive Threshold Parameter Estimation with Recursive Differential Grouping for Problem Decomposition", in Proceedings of the 2018 Conference on Genetic and Evolutionary Computation Conference (GECCO), Kyoto, Japan, ACM, pp.889 - 896, 2018.
  29. Haqqani, M., Li, X. and Yu, X. (2018), "Multi-objective Journey Planning under Uncertainty: A Genetic Approach", in Proceedings of the 2018 Conference on Genetic and Evolutionary Computation Conference (GECCO), Kyoto, Japan, ACM, pp.1262 - 1269, 2018.
  30. Kenny, A., Li, X. and Ernst, A.T. (2018), "A Merge Search Algorithm and its Application to the Constrained Pit Problem in Mining", in Proceedings of the 2018 Conference on Genetic and Evolutionary Computation Conference (GECCO), Kyoto, Japan, ACM, pp.316 - 323, 2018.
  31. Al-Zubaidi,W.H.A., Dam, H.K., Ghose, A., Li, X., "Multi-objective search-based approach to estimate issue resolution time", in Proceedings of the 13th International Conference on Predictive Models and Data Analytics in Software Engineering, ACM, pp. 53 - 62, 2017.
  32. Kenny, A., Li, X. (2017), "A Study on Pre-training Deep Neural Networks Using Particle Swarm Optimisation", in Proceedings of the tenth International Conference on Simulated Evolution and Learning (SEAL'17), LNCS 10593, pp.361 - 372, 2017.
  33. Lin, J., Luo, D., Li, X., Gao, K., Liu, Y. (2017), "Differential Evolution Based Hyper-heuristic for the Flexible Job-Shop Scheduling Problem with Fuzzy Processing Time", in Proceedings of the tenth International Conference on Simulated Evolution and Learning (SEAL'17), LNCS 10593, pp.75 - 86, 2017.
  34. Duan, Q., Shao, C., Li, X., Shi, Y. (2017), "Visualizing the Search Dynamics in a High-Dimensional Space for a Particle Swarm Optimizer", in Proceedings of the tenth International Conference on Simulated Evolution and Learning (SEAL'17), LNCS 10593, pp.994 - 1002, 2017.
  35. Schellenberg, S., Li, X., and Michalewicz, Z., (2017), "Preliminary Study on Solving Coal Processing and Blending Problems Using Lexicographic Ordering", in Proceedings of the 30th Australiasian Conference on Artificial Intelligence (AI'17), LNCS 10400, pp.221-233, 2017.
  36. Demediuk, S., Tamassia, M., Raffe, W., Zambetta, F., Li, X., Mueller, F. (2017),"Monte Carlo Tree Search Based Algorithms for Dynamic Difficulty Adjustment", in Proceedings of the Conference on Computational Intelligence and Games (CIG 2017), IEEE, pp.53-59, 2017.
  37. Islam, M.J., Li, X. and Deb, K., (2017), "Multimodal Truss Structure Design Using Bilevel and Niching Based Evolutionary Algorithms", in Proceedings of the 2017 Conference on Genetic and Evolutionary Computation Conference (GECCO), Berlin, Germany, ACM, pp.274-287, 2017.
  38. Kenny, A., Li, X., Ernst, A.T. and Thiruvady, D., (2017), "Towards Solving Large-Scale Precedence Constrained Production Scheduling Problems in Mining", in Proceedings of the 2017 Conference on Genetic and Evolutionary Computation Conference (GECCO), Berlin, Germany, ACM, pp.1137-1144, 2017.
  39. Haqqani, M., Li, X. and Yu, X. (2017), ``An Evolutionary Multi-criteria Journey Planning Algorithm for Multimodal Transportation Networks'', in Proceedings of the Australasian Conference on Artificial Life and Computational Intelligence (ACALCI) , LNCS 10142, pp.144-156, 2017.
  40. Haqqani, M., Li, X. and Yu, X. (2017), ``Estimating Passenger Preferences Using Implicit Relevance Feedback for Personalized Journey Planning'', in Proceedings of the Australasian Conference on Artificial Life and Computational Intelligence (ACALCI), LNCS 10142, pp.157-168, 2017.
  41. Qi, Y., Guo, H., and Li, X. (2017), ``Extending the Delaunay Triangulation Based Density Measurement to Many-Objective Optimization'', in Proceedings of the Australasian Conference on Artificial Life and Computational Intelligence (ACALCI), LNCS 10142, pp.3-11, 2017.
  42. Fico, F., Urbino, F., Carrese, R., Marzocca, P., and Li, X. (2017), ``Surrogate-Assisted Multi-swarm Particle Swarm Optimization of Morphing Airfoils'', in Proceedings of the Australasian Conference on Artificial Life and Computational Intelligence (ACALCI), LNCS 10142, pp.124-133, 2017.
  43. Miller, P., Colasante, M. and Li, X. (2016), ``Debugging performance: creative solutions to developing computer science students' problemsolving skills'', in Proceedings of the Annual Conference of the Higher Education Research and Development Society of Australasia (HERDSA 2016), New South Wales, Australia, 4-7 July 2016, pp.1-11, 2016.
  44. Tamassia, M., Zambetta, F., Raffe, W., Mueller, F., Li, X. (2016), ``Dynamic Choice of State Abstraction in Q-learning,'' in Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI 2016), The Hague, Neitherland, pp.46 -54, 2016.
  45. Schellenberg, S., Li, X., and Michalewicz, Z., (2016), ``Benchmarks for the coal processing and blending,'' in Proceedings of the 2016 Conference on Genetic and Evolutionary Computation Conference (GECCO), (Denver, USA), ACM, pp.1005 -1012, 2016.
  46. Kenny, A., Li, X., Qin, K., and Ernst, A., (2016), ``A Population-based Local Search Technique with Random Descent and Jump for the Steiner Tree Problem in Graphs,'' in Proceedings of the 2016 Conference on Genetic and Evolutionary Computation Conference (GECCO), (Denver, USA), ACM, pp.333-340, 2016.
  47. Omidvar, M., Kazimipour, B., Li, X. and Yao, X., (2016), ``CBCC3 - A Contribution-Based Cooperative Coevolutionary Algorithm with Better Exploration/Exploitation Balance'', in Proceedings of Congress of Evolutionary Computation (CEC 2016), IEEE, pp.3541-3548, 2016.
  48. Qi, Y., Yin, M. and Li, X. (2016), "A Delaunay Triangulation Based Density Measurement for Evolutionary Multi-objective Optimization", in Proceedings of the Australasian Conference on Artificial Life and Computational Intelligence (ACALCI '16), LNCS 9592, pp.183--192, 2016.
  49. Ghasemishabankareh, B., Shahsavari-Pour, N., Basiri, M.and Li, X. (2016), "A Hybrid Imperialist Competitive Algorithm for the Flexible Job Shop Problem", in Proceedings of the Australasian Conference on Artificial Life and Computational Intelligence (ACALCI '16), LNCS 9592, pp.221--233, 2016.
  50. Li, N., Cheung, Sherman, Li, X. and Tu, J. (2015), "Development of a multi-objective design optimization platform using NSM-PSO and CFD for heating and ventilation applications", in Proceedings of the Eleventh International Conference on CFD in the Minerals and Process Industries, pp.1--6, 2015.
  51. Li, N., Cheung, S., Li, X., and Tu, J., "Multi-objective optimization of thermal comfort and energy consumption in a typical office room using CFD and NSM-PSO," in Proceeding of the 21st International Congress on Modelling and Simulation (MODSIM2015), pp.78--84, December 2015.
  52. Raffe, W., Zambetta, F., Tamassia, M., Mueller, F., Pell, S. and Li, X. (2015), "Player-Computer Interaction Features for Designing Digital Play Experiences across Six Degrees of Water Contact", in Proceedings of CHI PLAY 2015, pp.295-305, 2015.
  53. Ivanovic, J., Raffe, W., Zambetta, F. & Li, X. (2015), "Combining Monte Carlo Tree Search and Apprenticeship Learning for Capture the Flag", in Proceedings of the Conference on Computational Intelligence and Games (CIG 2015), IEEE, pp.154-161, 2015.
  54. Raffe, W. Zambetta, F., Tamassia, M., Mueller, F. and Li, X. (2015), "Enhancing Theme Park Experiences through Adaptive Cyber-Physical Play", in Proceedings of the Conference on Computational Intelligence and Games (CIG 2015), IEEE, pp.503-510, 2015.
  55. Kazimipour, B., Omidvar, M., Li, X. and Qin, A.K., (2015), "A Sensitivity Study of Contribution-Based Cooperative Co-evolutionary Algorithms", in Proceedings of Congress of Evolutionary Computation (CEC 2015), IEEE, pp.417-422, 2015
  56. Xie, J., Mei, Y., Ernst, A., Li, X. and Song, A., (2015), "A Restricted Neighbourhood Tabu Search for Storage Location Assignment Problem", in Proceedings of Congress of Evolutionary Computation (CEC 2015), IEEE, pp.2805-2812, 2015.
  57. Mohammadi, A., Omidvar, M., Li, X. and Deb, K. (2015), "Sensitivity Analysis of Penalty-based Boundary Intersection on Aggregation-based EMO Algorithms", in Proceedings of Congress of Evolutionary Computation (CEC 2015), IEEE, pp.2891-2898, 2015.
  58. G. Yu, H. Jin and X. Li, (2015), "An Improved Performance Metric for Multiobjective Evolutionary Algorithms with User Preferences", in Proceedings of Congress of Evolutionary Computation (CEC 2015), IEEE, pp.908-915, 2015.
  59. Mei, Y. Li, X., Salim, F., and Yao, X., "Heuristic Evolution with Genetic Programming for Traveling Thief Problem," in Proceedings of the 2015 IEEE Congress on Evolutionary Computation (CEC), IEEE, pp.2753--2760, 2015.
  60. Kazimipour, B., Li, X. and Qin, A.K. (2014), "Why Advanced Population Initialization Techniques Perform Poorly in High Dimensions?" in Proceedings of the tenth International Conference on Simulated Evolution and Learning (SEAL'14), 2014, pp.479 - 490.
  61. Mei, Y., Li, X. and Yao, X. (2014), "Improving Efficiency of Heuristics for the Large Scale Traveling Thief Problem", in Proceedings of the tenth International Conference on Simulated Evolution and Learning (SEAL'14), 2014, pp.631 - 643.
  62. Xie, J., Mei, Y., Ernst, A., Li, X. and Song, A. (2014), "Scaling Up Solutions to Storage Location Assignment Problems by Genetic Programming", in Proceedings of the tenth International Conference on Simulated Evolution and Learning (SEAL'14), 2014, pp.691 - 702.
  63. Haqqani, M., Li, X. and Yu, X. (2014), "A Multi-Objective A* Search Based on Non-dominated Sorting", in Proceedings of the tenth International Conference on Simulated Evolution and Learning (SEAL'14), 2014, pp.228 - 238.
  64. Kazimipour, B., Omidvar, M., Li, X. and Qin, A.K. (2014), "A Novel Hybridization of Opposition-based Learning and Cooperative Co-evolutionary for Large-Scale Optimization". In Proceedings of Congress of Evolutionary Computation (CEC 2014), IEEE, 2014, pp.2833 - 2840.
  65. Kazimipour, B., Li, X. and Qin, A.K. (2014), "Effects of Population Initialization on Differential Evolution for Large Scale Optimization". In Proceedings of Congress of Evolutionary Computation (CEC 2014), IEEE, 2014, pp.2404 - 2411.
  66. Kazimipour, B., Li, X. and Qin, A.K. (2014), "A Review of Population Initialization Techniques for Evolutionary Algorithms". In Proceedings of Congress of Evolutionary Computation (CEC 2014), IEEE, 2014, pp.2585 - 2592.
  67. Xie, J., Mei, Y., Ernst, A., Li, X. and Song, A. (2014), "A Genetic Programming-based Hyper-heuristic Approach for Storage Location Assignment Problem". In Proceedings of Congress of Evolutionary Computation (CEC 2014), IEEE, 2014, p.301 - 307.
  68. Mohammadi, A., Omidvar, M., Li, X. and Deb, K. (2014), "Integrating User Preferences and Decomposition methods for Many-objective Optimization". In Proceedings of Congress of Evolutionary Computation (CEC 2014), IEEE, 2014, p.421 - 428.
  69. Omidvar, M., Mei, Y. and Li, X. (2014), "Effective Decomposition of Large-Scale Separable Continuous Functions for Cooperative Co-evolutionary Algorithms". In Proceedings of Congress of Evolutionary Computation (CEC 2014), IEEE, 2014, p.1305 - 1312 .
  70. Mei, Y., Li, X. and Yao, X. (2014), "Variable Neighborhood Decomposition for Large Scale Capacitated Arc Routing Problem". In Proceedings of Congress of Evolutionary Computation (CEC 2014), IEEE, 2014, pp.1313 - 1320 .
  71. Lee, G., Luo, M., Zambetta, F. and Li, X. (2014), "Learning a Super Mario Controller from Examples of Human Play". In Proceedings of Congress of Evolutionary Computation (CEC 2014), IEEE, 2014, p.1 - 8.
  72. Raffe, W.,Zambetta, F. and Li, X. (2013), " Neuroevolution of Content Layout in the PCG: Angry Bots Video Game", in Proceedings of Congress of Evolutionary Computation (CEC 2013), IEEE, pp.673 - 680.
  73. Mei, Y., Li, X. and Yao, X. (2013), "Decomposing Large-Scale Capacitated Arc Routing Problems using a Random Route Grouping Method", in Proceedings of Congress of Evolutionary Computation (CEC 2013), IEEE, pp.1013 - 1020.
  74. Epitropakis, M., Li, X. and Burke, E. (2013), "A Dynamic Archive Niching Differential Evolution algorithm for Multimodal Optimization", in Proceedings of Congress of Evolutionary Computation (CEC 2013), IEEE, pp.79 - 86.
  75. Kazimipour, B., Li, X. and Qin, A.K. (2013), "Initialization Methods for Large Scale Global Optimization", in Proceedings of Congress of Evolutionary Computation (CEC 2013), IEEE, p.2750 - 2757.
  76. Qin, A.K. and Li, X. (2013), "Differential Evolution on the CEC-2013 Single-Objective Continuous Optimization Testbed", in Proceedings of Congress of Evolutionary Computation (CEC 2013), IEEE, p.1099 - 1106.
  77. Qin, A.K. and Li, X. (2013), "Investigation of Self-adaptive Differential Evolution on the CEC-2013 Single-Objective Continuous Optimization Testbed", in Proceedings of Congress of Evolutionary Computation (CEC 2013), IEEE, pp.1107 -1114.
  78. Mohammadi, A., Omidvar, M. and Li, X. (2013), "A New Performance Metric for User-preference Based Multi-objective Evolutionary Algorithms", in Proceedings of Congress of Evolutionary Computation (CEC 2013), IEEE, pp.2825 - 2832.
  79. Mohammadi, A., Omidvar, M. and Li, X. (2012), "Reference Point Based Multi-objective Optimization Through Decomposition", in Proceedings of Congress of Evolutionary Computation (CEC 2012), IEEE, pp.1150 - 1157 (source code).
  80. Raffe, W.,Zambetta, F. and Li, X. (2012), "A Survey of Procedural Terrain Generation Techniques using Evolutionary Algorithms", in Proceedings of Congress of Evolutionary Computation (CEC 2012), IEEE, pp.2090 - 2097.
  81. Raffe, W.,Zambetta, F. and Li, X. (2011), "Evolving Patch-based Terrains for Use in Video Games", in Proceeding of Genetic and Evolutionary Computation Conference (GECCO'11), ACM Press, pp.363 - 370.
  82. Omidvar, M.,Li, X. and Yao, X. (2011), "Smart Use of Computational Resource Based on Contribution for Cooperative Co-evolutionary Algorithms", in Proceeding of Genetic and Evolutionary Computation Conference (GECCO'11), ACM Press, pp.1115 - 1122.
  83. Carrese, R., Winarto, H., and Li, X. (2011), "An efficient strategy to incorporate designer-preferences in automated airfoil design", in Proceeding of the Fourteenth Australian International Aerospace Congress (AIAC14), Melbourne, Australia, 2011 (accepted on 10/12/2010).
  84. Carrese, R., Winarto, H., and Li, X. (2011), "Integrating user-preference swarm algorithm and surrogate modeling for airfoil design", in Proceeding of the 49th AIAA Aerospace Sciences Meeting, Orlando, Florida, AIAA-2011-1246.
  85. Zhai, Z. Li, X. (2011), "A Dynamic Archive Based Niching Particle Swarm Optimizer Using a Small Population Size", in Proceedings of the Australian Computer Science Conference (ACSC 2011), Vol. 113, M. Reynolds, Ed.
  86. Lin, D., Li. X., and Wang, D. (2011), "Atavistic Strategy for Genetic Algorithm", in Proceeding of Advances in Swarm Intelligence - Second International Conference (ICSI 2011), Part I,LNCS6728, Springer, pp.497-505.
  87. Omidvar, M.,Li, X.. (2010), "A Comparative Study of CMA-ES on Large Scale Global Optimisation", in Proceedings of the 23rd Australasian Joint Conference on Artificial Intelligence (AI'10), LNAI 6464, Springer, pp. 303 - 312.
  88. Donate, J.P., Li, X. Gutierrez, G. and Sanchis, A. (2010), "Time series forecasting by evolving artificial neural networks using genetic algorithms and differential evolution", in Proceedings of 2010 International Joint Conference on Neural Networks (IJCNN 2010), IEEE, p3999 - 4006.
  89. Omidvar, M.,Li, X., Yao, X. and Yang, Z. (2010), "Cooperative Co-evolution for Large Scale Optimization Through More Frequent Random Grouping", in Proceedings of Congress of Evolutionary Computation (CEC 2010), IEEE, pp.1754 - 1761.
  90. Omidvar, M.,Li, X. and Yao, X. (2010), "Cooperative Co-evolution with Delta Grouping for Large Scale Non-separable Function Optimization", in Proceedings of Congress of Evolutionary Computation (CEC 2010), IEEE, pp.1762 - 1769.
  91. Li, J., Li, X. and Wood, A. (2010), "Species-based Evolutionary Algorithms for Multimodal Functions: A brief review", in Proceedings of Congress of Evolutionary Computation (CEC 2010), IEEE, pp.4156 - 4163.
  92. Li, X. and Deb, K. (2010), "Comparing lbest PSO Niching algorithms Using Different Position Update Rules", in Proceedings of Congress of Evolutionary Computation (CEC 2010), IEEE, pp.1564 - 1571.
  93. Wickramasinghe, W., Carrese, R. and Li, X. (2010), "Designing Airfoils using a Reference Point based Evolutionary Many-objective Particle Swarm Optimization Algorithm", in Proceedings of Congress of Evolutionary Computation (CEC 2010), IEEE, pp.1857 - 1864.
  94. Wickramasinghe, W. and Li, X. (2009), "A Distance Metric for Evolutionary Many-Objective Optimization Algorithms using User-Preferences", in Proceedings of the 22nd Australasian Joint Conference on Artificial Intelligence (AI'09) , Lecture Notes in Computer Science (LNCS 5866), Springer, p443 - 453.
  95. Jaehne, M., Branke, J. and Li, X. (2009), "Evolutionary Algorithms and Multi-Objectivization for the Travelling Salesman Problem", in Proceeding of Genetic and Evolutionary Computation Conference (GECCO'09), ACM Press, p.595 - 602.
  96. Wickramasinghe, W. and Li, X. (2009), "Using a Distance Metric to Guide PSO Algorithms for Many-Objective Optimization", in Proceeding of Genetic and Evolutionary Computation Conference (GECCO'09), ACM Press, p667- 674.
  97. Li, X. and Yao, X. (2009), "Tackling High Dimensional Nonseparable Optimization Problems By Cooperatively Coevolving Particle Swarms",in Proceedings of Congress of 2009 Evolutionary Computation (CEC'09), pp.1546 - 1553.
  98. Li, L., Li, X., Yu, X. and Guo, W. (2009), "A Modified PSO Algorithm for Constrained Multi-Objective Optimization", in NSS: 2009 3rd International conference on Network and System Security, p.462-467, IEEE.
  99. Allmendinger, R., Li, X. and Branke, J. (2008), "Reference Point-Based Particle Swarm Optimization Using a Steady-State Approach", in Proceedings of the seventh International Conference on Simulated Evolution and Learning (SEAL'08), Lecture Notes in Computer Science (LNCS 5361), Springer, pp.200 - 209.
  100. Ronkkonen, J., Li, X., Kyrki, V. and Lampinen, J. (2008), "A Generator for Multimodal Test Functions with Multiple Global Optima", in Proceedings of the seventh International Conference on Simulated Evolution and Learning (SEAL'08), Lecture Notes in Computer Science (LNCS 5361), Springer, pp.239 - 248.
  101. Wickramasinghe, W. and Li, X. (2008), "Choosing Leaders for Multi-objective PSO Algorithms using Differential Evolution", in Proceedings of the seventh International Conference on Simulated Evolution and Learning (SEAL'08), Lecture Notes in Computer Science (LNCS 5361), Springer, pp.249 - 258.
  102. Iorio, A. and Li, X. (2008), "Improving the Performance and Scalability of Differential Evolution", in Proceedings of the seventh International Conference on Simulated Evolution and Learning (SEAL'08), Lecture Notes in Computer Science (LNCS 5361), Springer, pp.131 - 140.
  103. Wickramasinghe, W. and Li, X. (2008), "Integrating User Preferences with Particle Swarms for Multi-objective Optimization", in Proceeding of Genetic and Evolutionary Computation Conference (GECCO'08), ACM Press, p.745 - 752.
  104. Li, L., Li, X., and Yu, X. (2008), "Power Generation Loading Optimization using a Multi-Objective Constraint-Handling Method via PSO Algorithm", in Proceedings of the IEEE International Conference on Industrial Informatics (INDIN 2008), DCC, Daejeon, Korea, July 13 - 16, 2008, pp.1362 - 1367.
  105. Li, L., Li, X., and Yu, X. (2008), "A Multi-objective Constraint-handling Method with PSO Algorithm for Constrained Engineering Optimization Problems", in Proceeding of Congress of 2008 Evolutionary Computation (CEC'08), IEEE Service Center, Piscataway, NJ 08855-1331, pp.1528-1535.
  106. Li, X., Branke, J. and Kirley, M. (2007), "On Performance Metrics and Particle Swarm Methods for Dynamic Multiobjective Optimization Problems", in Proceeding of Congress of 2007 Evolutionary Computation (CEC'07), IEEE Service Center, Piscataway, NJ 08855-1331, pp.1635 - 1643.
  107. Bird, S. and Li, X. (2007), "Using Regression to Improve Local Convergence", in Proceedings of Congress of 2007 Evolutionary Computation (CEC'07), p.1555 - 1562, IEEE Service Center, Piscataway, NJ 08855-1331 (source code).
  108. Li, X., Branke, J. and Kirley, M. (2007), "Performance Metrics and Particle Swarm Methods for Dynamic Multiobjective Optimization Problems", in Proceeding of Genetic and Evolutionary Computation Conference 2007 (GECCO'07), eds. Thierens, D., pp.906, ACM Press.
  109. Li, X. (2007), "A Multimodal Particle Swarm Optimizer Based on Fitness Euclidean-distance Ratio", in Proceeding of Genetic and Evolutionary Computation Conference 2007 (GECCO'07), eds. Thierens, D., pp.78 - 85, ACM Press.
  110. Bird, S. and Li, X. (2007), "Informative Performance Metrics for Dynamic Optimization Problems", in Proceeding of Genetic and Evolutionary Computation Conference 2007 (GECCO'07), eds. Thierens, D., pp.18 - 25, ACM Press.
  111. Iorio, A and Li, X. (2006), "Rotationally Invariant Crossover Operators in Evolutionary Multiobjective Optimization", in Proceeding ofthe Sixth International Conference on Simulated Evolution And Learning (SEAL'06), LNCS 4247, eds. Wang, T.-D., Li, X., et al., pp.181-188 (© Springer-Verlag) (view PDF).
  112. Li, X., Branke, J. and Blackwell, T. (2006), "Particle Swarm with Speciation and Adaptation in a Dynamic Environment ", in Proceeding of Genetic and Evolutionary Computation Conference 2006 (GECCO'06), eds. M. Keijzer, et al., pp.51 - 58, ACM Press. (nominated for a best paper award).
  113. Iorio, A and Li, X. (2006), "Rotated Test Problems for Assessing the Performance of Multiobjective Optimization Algorithms", in Proceeding of Genetic and Evolutionary Computation Conference 2006 (GECCO'06), eds. M. Keijzer, et al., pp.683 - 690, ACM Press (view PDF).
  114. Iorio, A and Li, X.(2006), "Incorporating Directional Information within a Differential Evolution Algorithm for Multiobjective Optimization", in Proceeding of Genetic and Evolutionary Computation Conference 2006 (GECCO'06), eds. M. Keijzer, et al., pp.691 - 697, ACM Press (view PDF).
  115. Bird, S. and Li, X.(2006), "Adaptively Choosing Niching Parameters in a PSO", in Proceeding of Genetic and Evolutionary Computation Conference 2006 (GECCO'06), eds. M. Keijzer, et al., p.3 - 9, ACM Press.
  116. Bird, S. and Li, X.(2006), "Enhancing the robustness of a speciation-based PSO", in Proceeding of Congress of 2006 Evolutionary Computation (CEC'06), pp.3185-3192, IEEE Service Center, Piscataway, NJ 08855-1331 (source code).
  117. Parrott, D., Li, X. and Ciesielski, V. (2005), "Multi-objective Techniques in Genetic Programming for Evolving Classifier Systems", in Proceeding of the 2005 Congress on Evolutionary Computation (CEC'05), pp.183 - 190, IEEE Service Center, Piscataway, NJ 08855-1331 (view PDF).
  118. Li, X. (2005), "Efficient Differential Evolution using Speciation for Multimodal Function Optimization", in Proceeding of Genetic and Evolutionary Computation Conference 2005 (GECCO'05), eds. Beyer, Hans-Georg et al., Washington DC, USA, 25-29 June, pp.873-880.
  119. Iorio, A. and Li, X. (2004), "Solving RotatedMulti-objective Optimization Problems Using Differential Evolution ",in Proceeding of the 17th Joint Australian Conference on Artificial Intelligence, Lecture Notes in Computer Science (LNCS 3339), eds. G.I. Webb and Xinghuo Yu, p.861-872 (view PDF) © Springer-Verlag).
  120. Iorio, A. and Li, X. (2004), "Solving RotatedMulti-objective Optimization Problems Using Differential Evolution ",in Proceeding of GECCO'04 Workshop on Self-organization in Representationfor Evolutionary Algorithms - Building Complexity from Simplicity, Genetic and Evolutionary Computation Conference 2004 (GECCO'04)
  121. Iorio, A. and Li, X. (2004), "A Cooperative Coevolutionary Multiobjective Algorithm Using Non-dominated Sorting",in Proceeding of Genetic and Evolutionary Computation Conference 2004 (GECCO'04), Lecture Notes in Computer Science (LNCS 3102), eds. Deb, K. et al., Seattle, USA, 26-30 June, pp.537-548 (view PDF) © Springer-Verlag).
  122. Li, X. (2004), "Adaptively Choosing Neighbourhood Bests using Species in a Particle Swarm Optimizer for Multimodal FunctionOptimization", in Proceeding of Genetic and Evolutionary Computation Conference 2004 (GECCO'04), Lecture Notes in Computer Science (LNCS 3102), eds. Deb, K. et al., Seattle, USA, 26-30 June, pp.105-116 (view PDF) © Springer-Verlag).
  123. Li, X. (2004), "Better Spread and Convergence: Particle Swarm Multiobjective Optimization using the Maximin FitnessFunction", in Proceeding of Genetic and Evolutionary Computation Conference 2004 (GECCO'04), Lecture Notes in Computer Science (LNCS 3102), eds. Deb, K. et al., Seattle, USA, 26-30 June, p.117-128 (view PDF) © Springer-Verlag).
  124. Bernstein, Y. Li, X., Ciesielski, V. and Song, A. (2004),"Improving Generalization Performance through Multiobjective ParsimonyEnforcement", in Proceeding of Genetic and Evolutionary Computation Conference 2004 (GECCO'04), Lecture Notes in Computer Science (LNCS 3103), eds. Deb, K. et al., Seattle, USA, 26-30 June, p.702-703© Springer-Verlag).
  125. Bernstein, Y. Li, X., Ciesielski, V. and Song, A. (2004),"Multiobjective Parsimony Enforcement for Superior GeneralizationPerformance",in Proceeding of the 2004 Congress on Evolutionary Computation (CEC'04), pp.83 - 89, IEEE Service Center, Piscataway, NJ 08855-1331 (view PDF).
  126. Parrott, D. and Li, X. (2004), "A Particle Swarm Model for Tracking Multiple Peaks in a Dynamic Environment usingSpeciation",in Proceeding of the 2004 Congress on Evolutionary Computation (CEC'04), pp.98 - 103, IEEE Service Center, Piscataway, NJ 08855-1331 (view PDF).
  127. Bernstein, Y. and Li, X. (2003),"Critical Dynamics in Evolutionary Algorithms",in Proceeding ofthe 2003 Congress on Evolutionary Computation (CEC'03), p.427-434, IEEE Service Center, Piscataway, NJ 08855-1331 (view PDF).
  128. Li, X. and Dam, K.H. (2003), "Comparing Particle Swarms for Tracking Extrema in Dynamic Environments",in Proceeding of the 2003 Congress on Evolutionary Computation (CEC'03), p.1772-1779, IEEE Service Center, Piscataway, NJ 08855-1331 (view PDF).
  129. Li, X. (2003), "A Non-dominated Sorting Particle Swarm Optimizer for Multiobjective Optimization", in Proceeding of Genetic and Evolutionary Computation Conference 2003(GECCO'03), Lecture Notes in Computer Science (LNCS 2723),eds. Erick Cantu-Paz et al., Chicago, USA, 12-16, July, 2003, pp.37-48(view PDF) (©Springer-Verlag)(Winner of 2013 ACM SIGEVO Impact Award).
  130. Li, X. (2003), "A real-coded predator-prey genetic algorithm for multiobjective optimization", in Proceeding of The Second International Conference on Evolutionary Multi-Criterion Optimization, Lecture Notes in Computer Science ( LNCS 2632), eds. C.M. Fonseca, P.J. Fleming, E. Zitzler, K. Deb, L. Thiele. p.207 -221(view PDF) (© Springer-Verlag)
  131. Gamble, T. and Li, X. (2002), "Emergence ofCooperation in the IPD Game using Spatial Interactions", in Proceeding of the Sixth Australia-Japan Joint Workshop on Intelligent and Evolutionary Systems, Canberra, Australia, pp.109-116.
  132. Li, X. and Sutherland, S. (2002), "A Cellular Genetic Algorithm Simulating Predator-Prey Interactions", in Proceeding of the 4th Asia-Pacific Conference on Simulated Evolution And Learning (SEAL'02), edited by Wang, L.,Tan, K.C.,Furuhashi,T., Kim, J-H and Yao, X. Singapore, pp.76-80 (view PDF).
  133. Iorio, A. and Li, X. (2002), "Parameter Control within a Co-operative Co-evolutionary Genetic Algorithm", in Proceeding of The Seventh International Conference on Parallel Problem Solving from Nature - PPSN VII, Lecture Notes in Computer Science (LNCS 2439), eds. Merelo Guervos, J.J., Adamidis, P., Beyer, H.G., Fernandez-Villacanas, J.L., and Schwefel, H.P., pp.247-256 (view PDF) (© Springer-Verlag).
  134. Li, X. and Kirley, M. (2002), "The Effects of Varying Population Density in a Fine-grained Parallel Genetic Algorithm", in Proceedings of the 2002 Congress on Evolutionary Computation (CEC'02), Volume: 2 , 2002, pp.1709 -1714.
  135. Li, X. and Magill, W. (2001), "Critical Density in a Fire Spread Model with Varied Environmental Conditions", in Proceeding of The Inaugural Workshop on Artificial Life, The 14th Australian Joint Conference on Artificial Intelligence, 10 - 14 December 2001, pp.27-39.
  136. Li, X. (2001), "Visualization of a Parallel Genetic Algorithm in Real Time", The Sixth International Computer Science Conference - Active Media Technology", LNCS 2252, 18-20 December 2001, Hong Kong, pp.335-346.
  137. Li, X. (2001), "Comparison of Neural Networks and an Optical Thin-Film Multilayer Model for Connectionist Learning", in Proceeding of INNS-IEEE International Joint Conference on Neural Networks, 14-19 July 2001, Washington, DC, p.1727-1732.
  138. Li, X. (2001), "Comparison of Neural Networks and an Optical Thin-Film Multilayer Model for Connectionist Learning", in Proceeding of. SCAI 2001, pp.111-122.
  139. Li, X. (2001), "Investigation on Critical Density in a Fire Spread Model using a Multi-agent Approach ", SwarmFest 2001, April 28 - 30, Santa Fe Institute, New Mexico.
  140. Li, X. (2001), "A Parallel Genetic Algorithm Implemented in Swarm", SwarmFest 2001, April 28 - 30, Santa Fe Institute, New Mexico.
  141. Magill, W. and Li, X. (2000), "Multi-agent Approach for Simulating Bush Fire Spread", The Sixth Pacific Rim International Conference on Artificial Intelligence (PRICAI 2000), Lecture Notes in Aritificial Intelligence 1886, edited by Mizoguchi, R. and Slaney, J., Springer, pp.814.
  142. Li, X. and.Wilson, B. (1999), "Modelling Watertable Fluctuations in Acid Sulphate Soils, Tweed Heads Using Artificial NeuralNetworks", in Proceeding of AI'99: Application Symoposium, 12th AustralianJoint Conference on Artificial Intelligence, pp.29-37.
  143. Li, X. and Purvis, M.K.(1998), "An Optical Thin-Film Multilayer Model For Connectionist Learning", in Proceedings of ICCIMA'98, the International Conference on Computational Intelligence and Multimedia Applications 1998, edited by Selvaraj, H. and Verma, B.World Scientific Publishing Co. Pte. Ltd., Singapore, pp.258-263.
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  145. Yamamoto, T., Kirley, M. and Li, X. (1998), "Species Abundance Adapted to the Energy Flow in Ecosystem Simulations." In R. Pfeifer et al. (eds) The Proceedings of The Fifth International Conference of The Society for Adapted Behaviour, MIT Press, pp.291-296.
  146. Yamamoto, T. and Li, X.(1998), "Non-linearly connected cross-scale interaction in a cellular network", in Proceedings of 1997 International Symposium on Nonlinear Theory and its Applications, vol. 2, Hawaii, pp.925-928.
  147. Li, X. (1997), "Using Genetic Algorithms for an Optical thin-Film Learning Model", in Proceedings of Australia-Japan Joint Workshop on Intelligent and Evolutionary Systems, Canberra, Australia, pp.126-130.
  148. Purvis, M.K. and Li, X.(1997), "Connectionist Learning Using an Optical Thin-Film Model", in Proceedings of the 15th World Congress on Scientific Computation, Modelling and Applied Mathematics - Artificial Intelligence and Computer Science, vol. 4, edited by Achim Sydow, Wissenschaft, and Technik Verlag, Berlin, pp. 239-244.
  149. Purvis, M.K. and Li, X. (1995), "Connectionist Learning Using Optical Thin-Film Model", in Proceeding of the 2nd New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, IEEE Computer Society Press, Los Alamitos, California, pp.63-66.
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Technical Reports

  1. Tang, K.,Li, X., Suganthan, P.N.,Yang, Z.and Weise, T. (2010), "Benchmark Functions for the CEC'2010 Special Session and Competition on Large Scale Global Optimization," Technical Report, Nature Inspired Computation and Applications Laboratory, USTC, China; URL:http://nical.ustc.edu.cn/cec10ss.php.
  2. Li, X., Tang, K., Omidvar, M.N., Yang, Z. and Qin, K., "Benchmark Functions for the CEC'2013 Special Session and Competition on Large Scale Global Optimization," Technical Report, Evolutionary Computation and Machine Learning Group, RMIT University, Australia, 2013 (Download benchmark suite source codes).
  3. Li, X., Engelbrecht, A. and Epitropakis, M.G., "Benchmark Functions for CEC'2013 Special Session and Competition on Niching Methods for Multimodal Function Optimization," Technical Report, Evolutionary Computation and Machine Learning Group, RMIT University, Australia, 2013 (Download benchmark suite source codes).
  4. Omidvar, M.N., Yang, M., Mei, Y. Li, X. and Yao, X., "IDG: A faster and more accurate differential grouping algorithm,'' University of Birmingham, School of Computer Science, Tech. Rep. CSR-15-04, September 2015.
  5. Omidvar, M.N., Yazdani, D., Branke, J. Li, X., Yang, S., Yao, X. "Generating Large-scale Dynamic Optimization Problem Instances Using the Generalized Moving Peaks Benchmark", Technical Report, arXiv:2107.11019, July 2021.

PhD. Thesis

Interested to read my Ph.D. thesis - "Connectionist Learning Architecture Based on an Optical Thin-Film Multilayer Model"? (view PDF)