Dr Kyle Harrison

Research Associate
School of Engineering and Information Technology

LOCATION

Room G01, Building 15, SEIT, UNSW Canberra at ADFA.

  • ABOUT
  • PUBLICATIONS

Kyle is a Research Associate with the School of Engineering and Information Technology at the University of New South Wales (UNSW), Canberra. He received his PhD in Computer Science from the University of Pretoria, South Africa, in 2018, and the M.Sc. and B.Sc. degrees in Computer Science from Brock University, Canada, in 2014 and 2012, respectively.

His research interests include computational intelligence, evolutionary computation, self-adaptation, fitness-landscape analysis, operations research, and real-world applications of complex networks. He has co-authored over 20 publications in top-tier journals and conferences and serves as a reviewer for various publication venues in the computational intelligence, evolutionary computation, and operations research domains.

Journal articles

Harrison KR; Ombuki-Berman BM; Engelbrecht AP, 2019, 'A parameter-free particle swarm optimization algorithm using performance classifiers', Information Sciences, vol. 503, pp. 381 - 400, http://dx.doi.org/10.1016/j.ins.2019.07.016

Ventresca M; Harrison KR; Ombuki-Berman BM, 2018, 'The bi-objective critical node detection problem', European Journal of Operational Research, vol. 265, pp. 895 - 908, http://dx.doi.org/10.1016/j.ejor.2017.08.053

Harrison KR; Engelbrecht AP; Ombuki-Berman BM, 2018, 'Self-adaptive particle swarm optimization: a review and analysis of convergence', Swarm Intelligence, vol. 12, pp. 187 - 226, http://dx.doi.org/10.1007/s11721-017-0150-9

Harrison KR; Engelbrecht AP; Ombuki-Berman BM, 2018, 'Optimal parameter regions and the time-dependence of control parameter values for the particle swarm optimization algorithm', Swarm and Evolutionary Computation, vol. 41, pp. 20 - 35, http://dx.doi.org/10.1016/j.swevo.2018.01.006

Harrison KR; Ventresca M; Ombuki-Berman BM, 2016, 'A meta-analysis of centrality measures for comparing and generating complex network models', Journal of Computational Science, vol. 17, pp. 205 - 215, http://dx.doi.org/10.1016/j.jocs.2015.09.011

Harrison KR; Engelbrecht AP; Ombuki-Berman BM, 2016, 'Inertia weight control strategies for particle swarm optimization: Too much momentum, not enough analysis', Swarm Intelligence, vol. 10, pp. 267 - 305, http://dx.doi.org/10.1007/s11721-016-0128-z

Conference Papers

Harrison KR; Ombuki-Berman B; Engelbrecht A, 2019, 'An Analysis of Control Parameter Importance in the Particle Swarm Optimization Algorithm', in Tan Y; Shi Y; Niu B (eds.), Advances in Swarm Intelligence, Springer, Cham, Chiang Mai, Thailand, pp. 93 - 105, presented at The Tenth International Conference on Swarm Intelligence (ICSI’2019), Chiang Mai, Thailand, 26 July 2019 - 30 July 2019, http://dx.doi.org/10.1007/978-3-030-26369-0_9

Harrison KR; Ombuki-Berman BM; Engelbrecht AP, 2019, 'The Parameter Configuration Landscape: A Case Study on Particle Swarm Optimization', in 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings, IEEE, pp. 808 - 814, presented at 2019 IEEE Congress on Evolutionary Computation (CEC), 10 June 2019 - 13 June 2019, http://dx.doi.org/10.1109/CEC.2019.8790242

Harrison KR; Ombuki-Berman BM; Engelbrecht AP, 2018, 'Gaussian-Valued Particle Swarm Optimization', in Dorigo M; Birattari M; Blum C; Christensen AL; Reina A; Trianni V (eds.), Swarm Intelligence, Springer Verlag, Rome, Italy, pp. 368 - 377, presented at Eleventh International Conference on Swarm Intelligence (ANTS 2018), Rome, Italy, 29 October 2018 - 31 October 2018, http://dx.doi.org/10.1007/978-3-030-00533-7_31

Harrison KR; Engelbrecht AP; Ombuki-Berman BM, 2018, 'An adaptive particle swarm optimization algorithm based on optimal parameter regions', in 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings, IEEE, Honolulu, HI, pp. 1 - 8, presented at IEEE Symposium Series on Computational Intelligence (IEEE SSCI), Honolulu, HI, 27 November 2017 - 01 December 2017, http://dx.doi.org/10.1109/SSCI.2017.8285342

Harrison KR; Ombuki-Berman BM; Engelbrecht AP, 2017, 'Optimal parameter regions for particle swarm optimization algorithms', in 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings, IEEE, SPAIN, pp. 349 - 356, presented at IEEE Congress on Evolutionary Computation (CEC), SPAIN, 05 June 2017 - 08 June 2017, http://dx.doi.org/10.1109/CEC.2017.7969333

Medland MR; Harrison KR; Ombuki-Berman BM, 2016, 'Automatic inference of graph models for directed complex networks using genetic programming', in 2016 IEEE Congress on Evolutionary Computation, CEC 2016, IEEE, Vancouver, CANADA, pp. 2337 - 2344, presented at IEEE Congress on Evolutionary Computation (CEC) held as part of IEEE World Congress on Computational Intelligence (IEEE WCCI), Vancouver, CANADA, 24 July 2016 - 29 July 2016, http://dx.doi.org/10.1109/CEC.2016.7744077

Harrison KR; Ombuki-Berman BM; Engelbrecht AP, 2016, 'A radius-free quantum particle swarm optimization technique for dynamic optimization problems', in 2016 IEEE Congress on Evolutionary Computation, CEC 2016, IEEE, Vancouver, CANADA, pp. 578 - 585, presented at IEEE Congress on Evolutionary Computation (CEC) held as part of IEEE World Congress on Computational Intelligence (IEEE WCCI), Vancouver, CANADA, 24 July 2016 - 29 July 2016, http://dx.doi.org/10.1109/CEC.2016.7743845

Harrison KR; Engelbrecht AP; Ombuki-Berman BM, 2016, 'The sad state of self-adaptive particle swarm optimizers', in 2016 IEEE Congress on Evolutionary Computation, CEC 2016, IEEE, Vancouver, CANADA, pp. 431 - 439, presented at IEEE Congress on Evolutionary Computation (CEC) held as part of IEEE World Congress on Computational Intelligence (IEEE WCCI), Vancouver, CANADA, 24 July 2016 - 29 July 2016, http://dx.doi.org/10.1109/CEC.2016.7743826

Ventresca M; Harrison KR; Ombuki-Berman BM, 2015, 'An Experimental Evaluation of Multi-Objective Evolutionary Algorithms for Detecting Critical Nodes in Complex Networks', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 164 - 176, http://dx.doi.org/10.1007/978-3-319-16549-3_14

Harrison KR; Ventresca M; Ombuki-Berman BM, 2015, 'Investigating Fitness Measures for the Automatic Construction of Graph Models', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 189 - 200, http://dx.doi.org/10.1007/978-3-319-16549-3_16

Harrison K; Ombuki-Berman BM; Engelbrecht AP, 2015, 'The effect of probability distributions on the performance of quantum particle swarm optimization for solving dynamic optimization problems', in Proceedings - 2015 IEEE Symposium Series on Computational Intelligence, SSCI 2015, IEEE, Cape Town, SOUTH AFRICA, pp. 242 - 250, presented at IEEE Symposium Series Computational Intelligence, Cape Town, SOUTH AFRICA, 07 December 2015 - 10 December 2015, http://dx.doi.org/10.1109/SSCI.2015.44

Medland MR; Harrison KR; Ombuki-Berman B, 2014, 'Incorporating expert knowledge in object-oriented genetic programming', in GECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference, ACM Press, pp. 145 - 146, presented at the 2014 conference companion, 12 July 2014 - 16 July 2014, http://dx.doi.org/10.1145/2598394.2598494

Medland MR; Harrison KR; Ombuki-Berman BM, 2014, 'Demonstrating the power of object-oriented genetic programming via the inference of graph models for complex networks', in 2014 6th World Congress on Nature and Biologically Inspired Computing, NaBIC 2014, IEEE, Porto, PORTUGAL, pp. 305 - 311, presented at 6th World Congress on Nature and Biologically Inspired Computing (NaBIC), Porto, PORTUGAL, 30 July 2014 - 01 August 2014, http://dx.doi.org/10.1109/NaBIC.2014.6921896

Harrison KR; Ombuki-Berman BM; Engelbrecht AP, 2014, 'Dynamic multi-objective optimization using charged vector evaluated particle swarm optimization', in Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014, IEEE, Beijing, PEOPLES R CHINA, pp. 1929 - 1936, presented at IEEE Congress on Evolutionary Computation (CEC), Beijing, PEOPLES R CHINA, 06 July 2014 - 11 July 2014, http://dx.doi.org/10.1109/CEC.2014.6900399

Harrison KR; Ombuki-Berman B; Engelbrecht AP, 2013, 'Knowledge transfer strategies for vector evaluated particle swarm optimization', in Purshouse RC; Fleming PJ; Fonesca CM; Greco S; Shaw J (eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), SPRINGER-VERLAG BERLIN, Sheffield, UNITED KINGDOM, pp. 171 - 184, presented at 7th International Conference on Eevolutionary Mmulti-Criterion Optimization (EMO), Sheffield, UNITED KINGDOM, 19 March 2013 - 22 March 2013, http://dx.doi.org/10.1007/978-3-642-37140-0_16

Harrison KR; Engelbrecht AP; Ombuki-Berman BM, 2013, 'A scalability study of multi-objective particle swarm optimizers', in 2013 IEEE Congress on Evolutionary Computation, CEC 2013, IEEE, Cancun, MEXICO, pp. 189 - 197, presented at IEEE Congress on Evolutionary Computation, Cancun, MEXICO, 20 June 2013 - 23 June 2013, http://dx.doi.org/10.1109/CEC.2013.6557570