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ORCIDBeatrice M. Ombuki-Berman
Beatrice M. Ombuki
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Journal Articles
- 2024
[j25]Nicholas Aksamit, Jinqiang Hou, Yifeng Li, Beatrice M. Ombuki-Berman:
Integrating transformers and many-objective optimization for drug design. BMC Bioinform. 25(1): 208 (2024)- [j24]Nicholas Aksamit, Alain Tchagang, Yifeng Li, Beatrice M. Ombuki-Berman:
Hybrid fragment-SMILES tokenization for ADMET prediction in drug discovery. BMC Bioinform. 25(1): 255 (2024) - [j23]Beatrice M. Ombuki-Berman:
Leonardo Vanneschi and Sara Silva: lectures on intelligent systems. Genet. Program. Evolvable Mach. 25(2): 23 (2024) - [j22]Alanna McNulty, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Decomposition and merging cooperative particle swarm optimization with random grouping for large-scale optimization problems. Swarm Intell. 18(2): 141-166 (2024) - [j21]Alanna McNulty, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
A comparative study of evolutionary algorithms and particle swarm optimization approaches for constrained multi-objective optimization problems. Swarm Evol. Comput. 91: 101742 (2024) - 2023
- [j20]Amirali Madani, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
Cooperative coevolutionary multi-guide particle swarm optimization algorithm for large-scale multi-objective optimization problems. Swarm Evol. Comput. 78: 101262 (2023) - 2022
- [j19]Pawel Jocko, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht
:
Multi-guide particle swarm optimisation archive management strategies for dynamic optimisation problems. Swarm Intell. 16(2): 143-168 (2022) - 2021
- [j18]Cody Dennis, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
An analysis of the impact of subsampling on the neural network error surface. Neurocomputing 466: 252-264 (2021) - 2020
- [j17]Beatrice M. Ombuki:
Juan C. Burguillo: Self-organizing coalitions for managing complexity. Genet. Program. Evolvable Mach. 21(1-2): 263-264 (2020) - [j16]Cody Dennis, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Random Regrouping and Factorization in Cooperative Particle Swarm Optimization Based Large-Scale Neural Network Training. Neural Process. Lett. 51(1): 759-796 (2020) - [j15]Cody Dennis, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
An Analysis of Activation Function Saturation in Particle Swarm Optimization Trained Neural Networks. Neural Process. Lett. 52(2): 1123-1153 (2020) - 2019
- [j14]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
A parameter-free particle swarm optimization algorithm using performance classifiers. Inf. Sci. 503: 381-400 (2019) - 2018
- [j13]Mario Ventresca, Kyle Robert Harrison, Beatrice M. Ombuki-Berman:
The bi-objective critical node detection problem. Eur. J. Oper. Res. 265(3): 895-908 (2018) - [j12]Kyle Robert Harrison, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
Self-adaptive particle swarm optimization: a review and analysis of convergence. Swarm Intell. 12(3): 187-226 (2018) - [j11]Kyle Robert Harrison, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
Optimal parameter regions and the time-dependence of control parameter values for the particle swarm optimization algorithm. Swarm Evol. Comput. 41: 20-35 (2018) - [j10]Justin Maltese, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
A Scalability Study of Many-Objective Optimization Algorithms. IEEE Trans. Evol. Comput. 22(1): 79-96 (2018) - 2016
- [j9]Kyle Robert Harrison, Mario Ventresca, Beatrice M. Ombuki-Berman:
A meta-analysis of centrality measures for comparing and generating complex network models. J. Comput. Sci. 17: 205-215 (2016) - [j8]Kyle Robert Harrison, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
Inertia weight control strategies for particle swarm optimization - Too much momentum, not enough analysis. Swarm Intell. 10(4): 267-305 (2016) - 2014
- [j7]Alexander Bailey, Mario Ventresca, Beatrice M. Ombuki-Berman:
Genetic Programming for the Automatic Inference of Graph Models for Complex Networks. IEEE Trans. Evol. Comput. 18(3): 405-419 (2014) - 2008
- [j6]Earl B. Foxwell, Beatrice M. Ombuki-Berman:
Particle swarm optimisation for the design of two-connected networks with bounded rings. Int. J. High Perform. Syst. Archit. 1(4): 220-230 (2008) - 2007
- [j5]Franklin Hanshar, Beatrice M. Ombuki-Berman:
Dynamic vehicle routing using genetic algorithms. Appl. Intell. 27(1): 89-99 (2007) - 2006
- [j4]Beatrice M. Ombuki, Brian Ross, Franklin Hanshar:
Multi-Objective Genetic Algorithms for Vehicle Routing Problem with Time Windows. Appl. Intell. 24(1): 17-30 (2006) - 2005
- [j3]Mario Ventresca, Beatrice M. Ombuki:
A Genetic Algorithm for the Design of Minimum-cost Two-connected Networks with Bounded Rings. Int. J. Comput. Intell. Appl. 5(2): 267-281 (2005) - 2004
- [j2]Beatrice M. Ombuki, Mario Ventresca:
Local Search Genetic Algorithms for the Job Shop Scheduling Problem. Appl. Intell. 21(1): 99-109 (2004) - 1998
- [j1]Morikazu Nakamura, Beatrice M. Ombuki, K. Shimabukuro, Kenji Onaga:
A new hybrid GA solution to combinatorial optimization problems - an application to the multiprocessor scheduling problem. Artif. Life Robotics 2(2): 74-79 (1998)
Conference and Workshop Papers
- 2024
- [c50]Ethan Gibbons, Beatrice M. Ombuki-Berman:
A Memetic Algorithm for Large-Scale Real-World Vehicle Routing Problems with Simultaneous Pickup and Delivery with Time Windows. MIC (1) 2024: 78-92 - [c49]Rasa Khosrowshahli, Shahryar Rahnamayan, Beatrice M. Ombuki-Berman:
Massive Dimensions Reduction and Hybridization with Meta-heuristics in Deep Learning. CCECE 2024: 469-475 - 2023
- [c48]Liam J. S. McDevitt, Kyle Robert Harrison, Beatrice M. Ombuki-Berman:
A Framework for Meta-heuristic Parameter Performance Prediction Using Fitness Landscape Analysis and Machine Learning. CEC 2023: 1-8 - [c47]Alanna McNulty, Beatrice M. Ombuki-Berman:
A Comparative Study of Multi-Guide Particle Swarm Optimization Topologies in Dynamic Multi-Objective Environments. CEC 2023: 1-10 - [c46]Tom Wallace, Beatrice M. Ombuki-Berman, Naser Ezzati-Jivan:
Identification and Classification of JMH Microbenchmark States using Time Series Analysis. ICPE (Companion) 2023: 101-105 - 2022
- [c45]Alanna McNulty, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Decomposition and Merging Co-operative Particle Swarm Optimization with Random Grouping. ANTS Conference 2022: 117-129 - [c44]Pawel Jocko, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Dynamic Multi-objective Optimisation Using Multi-guide Particle Swarm Optimisation. CEC 2022: 1-10 - [c43]Liam J. S. McDevitt, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
A Particle Swarm Optimization Decomposition Strategy for Large Scale Global Optimization. SSCI 2022: 1574-1581 - [c42]Mitchell Clark, Beatrice M. Ombuki-Berman, Nicholas Aksamit, Andries P. Engelbrecht:
Cooperative Particle Swarm Optimization Decomposition Methods for Large-scale Optimization. SSCI 2022: 1582-1591 - 2021
- [c41]Amirali Madani, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Decision Space Scalability Analysis of Multi-Objective Particle Swarm Optimization Algorithms. CEC 2021: 2179-2186 - [c40]Cody Dennis, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Predicting Particle Swarm Optimization Control Parameters From Fitness Landscape Characteristics. CEC 2021: 2289-2298 - [c39]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Visualizing and Characterizing the Parameter Configuration Landscape of Particle Swarm Optimization using Physical Landform Classification. CEC 2021: 2299-2306 - [c38]Tyler Crane, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
Two Modified NichePSO Algorithms for Multimodal Optimization. ICSI (1) 2021: 232-243 - 2020
- [c37]Reginald McLean, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Swarm Based Algorithms for Neural Network Training. SMC 2020: 2585-2592 - [c36]James Paterson, Beatrice M. Ombuki-Berman:
A Hybrid Approach to Network Robustness Optimization using Edge Rewiring and Edge Addition. SMC 2020: 4051-4057 - [c35]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Visualizing and Characterizing the Parameter Configuration Landscape of Differential Evolution using Physical Landform Classification. SSCI 2020: 2437-2444 - 2019
- [c34]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
The Parameter Configuration Landscape: A Case Study on Particle Swarm Optimization. CEC 2019: 808-814 - [c33]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
An Analysis of Control Parameter Importance in the Particle Swarm Optimization Algorithm. ICSI (1) 2019: 93-105 - 2018
- [c32]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Gaussian-Valued Particle Swarm Optimization. ANTS Conference 2018: 368-377 - [c31]James Paterson, Beatrice M. Ombuki-Berman:
Optimizing Scale-Free Network Robustness with the Great Deluge Algorithm. IEA/AIE 2018: 434-446 - 2017
- [c30]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Optimal parameter regions for particle swarm optimization algorithms. CEC 2017: 349-356 - [c29]Kyle Robert Harrison, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
An adaptive particle swarm optimization algorithm based on optimal parameter regions. SSCI 2017: 1-8 - [c28]Audrey Opoku-Amankwaah, Beatrice M. Ombuki-Berman:
An age layered population structure genetic algorithm for the multi-depot vehicle problem. SSCI 2017: 1-8 - 2016
- [c27]Kyle Robert Harrison, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
The sad state of self-adaptive particle swarm optimizers. CEC 2016: 431-439 - [c26]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
A radius-free quantum particle swarm optimization technique for dynamic optimization problems. CEC 2016: 578-585 - [c25]Michael Richard Medland, Kyle Robert Harrison, Beatrice M. Ombuki-Berman:
Automatic inference of graph models for directed complex networks using genetic programming. CEC 2016: 2337-2344 - [c24]Justin Maltese, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Pareto-based many-objective optimization using knee points. CEC 2016: 3678-3686 - 2015
- [c23]Derek Dibblee, Justin Maltese, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Vector-evaluated particle swarm optimization with local search. CEC 2015: 187-195 - [c22]Ron Bond, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
Evaluating landscape characteristics of dynamic benchmark functions. CEC 2015: 1343-1350 - [c21]Mario Ventresca, Kyle Robert Harrison, Beatrice M. Ombuki-Berman:
An Experimental Evaluation of Multi-objective Evolutionary Algorithms for Detecting Critical Nodes in Complex Networks. EvoApplications 2015: 164-176 - [c20]Kyle Robert Harrison, Mario Ventresca, Beatrice M. Ombuki-Berman:
Investigating Fitness Measures for the Automatic Construction of Graph Models. EvoApplications 2015: 189-200 - [c19]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
The Effect of Probability Distributions on the Performance of Quantum Particle Swarm Optimization for Solving Dynamic Optimization Problems. SSCI 2015: 242-250 - [c18]Justin Maltese, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Co-operative Vector-Evaluated Particle Swarm Optimization for Multi-objective Optimization. SSCI 2015: 1294-1301 - [c17]Justin Maltese, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
High-Dimensional Multi-Objective Optimization Using Co-operative Vector-Evaluated Particle Swarm Optimization with Random Variable Grouping. SSCI 2015: 1302-1309 - 2014
- [c16]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Dynamic multi-objective optimization using charged vector evaluated particle swarm optimization. IEEE Congress on Evolutionary Computation 2014: 1929-1936 - [c15]Michael Richard Medland, Kyle Robert Harrison, Beatrice M. Ombuki-Berman:
Incorporating expert knowledge in object-oriented genetic programming. GECCO (Companion) 2014: 145-146 - [c14]Michael Richard Medland, Kyle Robert Harrison, Beatrice M. Ombuki-Berman:
Demonstrating the power of object-oriented genetic programming via the inference of graph models for complex networks. NaBIC 2014: 305-311 - 2013
- [c13]Kyle Robert Harrison, Andries P. Engelbrecht, Beatrice M. Ombuki-Berman:
A scalability study of multi-objective particle swarm optimizers. IEEE Congress on Evolutionary Computation 2013: 189-197 - [c12]Kyle Robert Harrison, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Knowledge Transfer Strategies for Vector Evaluated Particle Swarm Optimization. EMO 2013: 171-184 - [c11]Mario Ventresca, Beatrice M. Ombuki-Berman, Andrew Runka:
Predicting Genetic Algorithm Performance on the Vehicle Routing Problem Using Information Theoretic Landscape Measures. EvoCOP 2013: 214-225 - [c10]Alexander Bailey, Beatrice M. Ombuki-Berman, Mario Ventresca:
Automatic inference of hierarchical graph models using genetic programming with an application to cortical networks. GECCO 2013: 893-900 - [c9]N. J. Unger, Beatrice M. Ombuki-Berman, Andries P. Engelbrecht:
Cooperative particle swarm optimization in dynamic environments. SIS 2013: 172-179 - 2012
- [c8]Alexander Bailey, Mario Ventresca, Beatrice M. Ombuki-Berman:
Automatic generation of graph models for complex networks by genetic programming. GECCO 2012: 711-718 - 2010
- [c7]Mohammad Naeem, Beatrice M. Ombuki-Berman:
An efficient genetic algorithm for the uncapacitated single allocation hub location problem. IEEE Congress on Evolutionary Computation 2010: 1-8 - 2009
- [c6]Joseph A. Brown, Sheridan K. Houghten, Beatrice M. Ombuki-Berman:
Genetic algorithm cryptanalysis of a substitution permutation network. CICS 2009: 115-121 - [c5]Andrew Runka, Beatrice M. Ombuki-Berman, Mario Ventresca:
A search space analysis for the waste collection vehicle routing problem with time windows. GECCO 2009: 1813-1814 - 2007
- [c4]Beatrice M. Ombuki-Berman, Mario Ventresca:
Search Difficulty of Two-Connected Ring-based Topological Network Designs. FOCI 2007: 267-274 - [c3]Mario Ventresca, Beatrice M. Ombuki-Berman:
Epistasis in Multi-Objective Evolutionary Recurrent Neuro-Controllers. ALIFE 2007: 77-84 - 2006
- [c2]Mario Ventresca, Beatrice M. Ombuki-Berman:
Search Space Analysis of Recurrent Spiking and Continuous-time Neural Networks. IJCNN 2006: 4514-4521 - 1998
- [c1]Beatrice M. Ombuki, Morikazu Nakamura, Kenji Onaga:
Experimental evaluation of an evolutionary scheduling scheme for the job shop scheduling problem. KES (3) 1998: 197-201
Parts in Books or Collections
- 2009
- [p1]Beatrice M. Ombuki-Berman, Franklin Hanshar:
Using Genetic Algorithms for Multi-depot Vehicle Routing. Bio-inspired Algorithms for the Vehicle Routing Problem 2009: 77-99
Informal and Other Publications
- 2024
- [i1]Rasa Khosrowshahli, Shahryar Rahnamayan, Beatrice M. Ombuki-Berman:
Massive Dimensions Reduction and Hybridization with Meta-heuristics in Deep Learning. CoRR abs/2408.07194 (2024)
Coauthor Index
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