| Self-adaptive particle swarm optimization: a review and analysis of convergence KR Harrison, AP Engelbrecht, BM Ombuki-Berman Swarm Intelligence 12, 187-226, 2018 | 136 | 2018 |
| Inertia weight control strategies for particle swarm optimization: Too much momentum, not enough analysis KR Harrison, AP Engelbrecht, BM Ombuki-Berman Swarm Intelligence 10, 267-305, 2016 | 109 | 2016 |
| Optimal parameter regions and the time-dependence of control parameter values for the particle swarm optimization algorithm KR Harrison, AP Engelbrecht, BM Ombuki-Berman Swarm and evolutionary computation 41, 20-35, 2018 | 70 | 2018 |
| The bi-objective critical node detection problem M Ventresca, KR Harrison, BM Ombuki-Berman European Journal of Operational Research 265 (3), 895-908, 2018 | 47 | 2018 |
| A parameter-free particle swarm optimization algorithm using performance classifiers KR Harrison, BM Ombuki-Berman, AP Engelbrecht Information Sciences 503, 381-400, 2019 | 41 | 2019 |
| An adaptive particle swarm optimization algorithm based on optimal parameter regions KR Harrison, AP Engelbrecht, BM Ombuki-Berman 2017 IEEE symposium series on computational intelligence (SSCI), 1-8, 2017 | 41 | 2017 |
| Portfolio optimization for defence applications KR Harrison, S Elsayed, I Garanovich, T Weir, M Galister, S Boswell, ... IEEE Access 8, 60152-60178, 2020 | 33 | 2020 |
| The sad state of self-adaptive particle swarm optimizers KR Harrison, AP Engelbrecht, BM Ombuki-Berman 2016 IEEE Congress on Evolutionary Computation (CEC), 431-439, 2016 | 32 | 2016 |
| Optimal parameter regions for particle swarm optimization algorithms KR Harrison, BM Ombuki-Berman, AP Engelbrecht 2017 IEEE congress on evolutionary computation (CEC), 349-356, 2017 | 31 | 2017 |
| An Experimental Evaluation of Multi-objective Evolutionary Algorithms for Detecting Critical Nodes in Complex Networks M Ventresca, KR Harrison, BM Ombuki-Berman Applications of Evolutionary Computation: 18th European Conference …, 2015 | 28 | 2015 |
| A meta-analysis of centrality measures for comparing and generating complex network models KR Harrison, M Ventresca, BM Ombuki-Berman Journal of computational science 17, 205-215, 2016 | 25 | 2016 |
| Knowledge transfer strategies for vector evaluated particle swarm optimization KR Harrison, B Ombuki-Berman, AP Engelbrecht Evolutionary Multi-Criterion Optimization: 7th International Conference, EMO …, 2013 | 24 | 2013 |
| Solving a novel multi-divisional project portfolio selection and scheduling problem KR Harrison, SM Elsayed, T Weir, IL Garanovich, SG Boswell, RA Sarker Engineering Applications of Artificial Intelligence 112, 104771, 2022 | 16 | 2022 |
| A hybrid multi-population approach to the project portfolio selection and scheduling problem for future force design KR Harrison, S Elsayed, IL Garanovich, T Weir, M Galister, S Boswell, ... IEEE Access 9, 83410-83430, 2021 | 16 | 2021 |
| The parameter configuration landscape: A case study on particle swarm optimization KR Harrison, BM Ombuki-Berman, AP Engelbrecht 2019 IEEE Congress on Evolutionary Computation (CEC), 808-814, 2019 | 15 | 2019 |
| A radius-free quantum particle swarm optimization technique for dynamic optimization problems KR Harrison, BM Ombuki-Berman, AP Engelbrecht 2016 IEEE Congress on Evolutionary Computation (CEC), 578-585, 2016 | 14 | 2016 |
| An analysis of control parameter importance in the particle swarm optimization algorithm KR Harrison, BM Ombuki-Berman, AP Engelbrecht International Conference on Swarm Intelligence, 93-105, 2019 | 13 | 2019 |
| An exploration of meta-heuristic approaches for the project portfolio selection and scheduling problem in a defence context KR Harrison, S Elsayed, T Weir, IL Garanovich, R Taylor, R Sarker 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 1395-1402, 2020 | 12 | 2020 |
| Multi-period project selection and scheduling for defence capability-based planning KR Harrison, S Elsayed, T Weir, IL Garanovich, M Galister, S Boswell, ... 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2020 | 11 | 2020 |
| Dynamic multi-objective optimization using charged vector evaluated particle swarm optimization KR Harrison, BM Ombuki-Berman, AP Engelbrecht 2014 IEEE Congress on Evolutionary Computation (CEC), 1929-1936, 2014 | 11 | 2014 |
Andries EngelbrechtStellenbosch University, Department of Industrial Engineering, and Division of Computer ScienceVerifierad e-postadress på sun.ac.za
