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Ed Keedwell
Person information
- affiliation: University of Exeter, College of Engineering, Mathematics and Physical Sciences, UK
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2020 – today
- 2024
- [c63]Aseel Ismael Ali
, Edward C. Keedwell
, Ayah Helal
:
A Differential Pheromone Grouping Ant Colony Optimization Algorithm for the 1-D Bin Packing Problem. GECCO 2024 - [c62]Darren M. Chitty
, James Charles
, Alberto Moraglio
, Ed Keedwell
:
Applying a Quantum Annealer to the Traffic Assignment Problem. GECCO 2024 - [c61]Darren M. Chitty, Ed Keedwell:
Greedy Strategies to Improve Phased Genetic Programming When Applied Directly to the Traveling Salesman Problem. GECCO Companion 2024: 491-494 - 2023
- [c60]Darren M. Chitty
, Ed Keedwell
:
Phased Genetic Programming for Application to the Traveling Salesman Problem. GECCO Companion 2023: 547-550 - [c59]Darren M. Chitty
, James Lewis
, Ed Keedwell
:
An Adaptive Sequence-Based Selection Hyper-Heuristic for Application to Electric Bus Scheduling. GECCO Companion 2023: 711-714 - [c58]Matthew Hayslep
, Edward C. Keedwell
, Raziyeh Farmani
:
Multi-Objective Multi-Gene Genetic Programming for the Prediction of Leakage in Water Distribution Networks. GECCO 2023: 1357-1364 - [c57]Darren M. Chitty
, James Lewis
, Ed Keedwell
:
Using a Parallel Ensemble of Sequence-Based Selection Hyper-Heuristics for Electric Bus Scheduling. GECCO Companion 2023: 1712-1720 - [c56]James Sakal
, Jonathan E. Fieldsend
, Edward C. Keedwell
:
Genotype Diversity Measures for Escaping Plateau Regions in University Course Timetabling. GECCO Companion 2023: 2090-2098 - [e1]Pierrick Legrand, Arnaud Liefooghe, Edward C. Keedwell, Julien Lepagnot, Lhassane Idoumghar, Nicolas Monmarché, Evelyne Lutton:
Artificial Evolution - 15th International Conference, Évolution Artificielle, EA 2022, Exeter, UK, October 31 - November 2, 2022, Revised Selected Papers. Lecture Notes in Computer Science 14091, Springer 2023, ISBN 978-3-031-42615-5 [contents] - 2022
- [c55]Darren M. Chitty, Ed Keedwell:
Defining a Quality Measure Within Crossover: An Electric Bus Scheduling Case Study. EA 2022: 73-88 - [c54]James Sakal
, Jonathan E. Fieldsend
, Edward C. Keedwell
:
Towards a Many-Objective Optimiser for University Course Timetabling. EA 2022: 133-144 - [c53]Amir Nasiri, Ed Keedwell, Raphaël Dorne, Mathias Kern, Gilbert Owusu:
A hyper-heuristic approach for the PDPTW. GECCO Companion 2022: 196-199 - [c52]Darren M. Chitty, William B. Yates, Ed Keedwell:
An edge quality aware crossover operator for application to the capacitated vehicle routing problem. GECCO Companion 2022: 419-422 - [c51]Clodomir J. Santana Jr., Edward C. Keedwell, Ronaldo Menezes:
Networks of evolution: modelling and deconstructing genetic algorithms using dynamic networks. GECCO Companion 2022: 459-462 - [c50]Ahmed Kheiri
, Edward C. Keedwell:
Selection hyper-heuristics. GECCO Companion 2022: 983-996 - [c49]Darren M. Chitty, William B. Yates, Ed Keedwell:
Using Evolutionary Routing Optimisation to Transition to Electric Vehicle Fleets. UKCI 2022: 489-501 - 2021
- [j21]Ahmed Kheiri
, Angeliki Gretsista, Ed Keedwell, Guglielmo Lulli, Michael G. Epitropakis, Edmund K. Burke:
A hyper-heuristic approach based upon a hidden Markov model for the multi-stage nurse rostering problem. Comput. Oper. Res. 130: 105221 (2021) - [j20]William B. Yates, Edward C. Keedwell:
Offline Learning with a Selection Hyper-Heuristic: An Application to Water Distribution Network Optimisation. Evol. Comput. 29(2): 187-210 (2021) - [j19]Shahin Jalili
, Samadhi Nallaperuma, Edward C. Keedwell, Alex Dawn, Laurence Oakes-Ash:
Application of metaheuristics for signal optimisation in transportation networks: A comprehensive survey. Swarm Evol. Comput. 63: 100865 (2021) - [c48]James Sakal, Jonathan E. Fieldsend, Edward C. Keedwell:
Learning assignment order in an ant colony optimiser for the university course timetabling problem. GECCO Companion 2021: 77-78 - [c47]Sabrina Draude, Edward C. Keedwell, Zoran Kapelan, Rebecca Hiscock:
Wastewater systems planned maintenance scheduling using multi-objective optimisation. GECCO Companion 2021: 309-310 - 2020
- [j18]Ahamed Fayeez Tuani, Edward C. Keedwell, Matthew Collett:
Heterogenous Adaptive Ant Colony Optimization with 3-opt local search for the Travelling Salesman Problem. Appl. Soft Comput. 97(Part B): 106720 (2020) - [c46]Clodomir J. Santana Jr., Edward C. Keedwell, Ronaldo Menezes:
An approach to assess swarm intelligence algorithms based on complex networks. GECCO 2020: 31-39 - [c45]Matthew Barrie Johns, Herman A. Mahmoud
, Edward C. Keedwell, Dragan A. Savic
:
Adaptive augmented evolutionary intelligence for the design of water distribution networks. GECCO 2020: 1116-1124 - [c44]Nicholas D. F. Ross
, Ed Keedwell
, Dragan A. Savic
:
Human-Derived Heuristic Enhancement of an Evolutionary Algorithm for the 2D Bin-Packing Problem. PPSN (2) 2020: 413-427
2010 – 2019
- 2019
- [j17]William B. Yates
, Edward C. Keedwell:
An analysis of heuristic subsequences for offline hyper-heuristic learning. J. Heuristics 25(3): 399-430 (2019) - [c43]Ethan Bunce, Edward C. Keedwell:
Optimisation of a Checkers Player Using Neural and Metaheuristic Approaches. EA 2019: 53-67 - [c42]William B. Yates, Edward C. Keedwell:
Analysing heuristic subsequences for offline hyper-heuristic learning. GECCO (Companion) 2019: 37-38 - [c41]Diane P. Fraser, Edward C. Keedwell, Stephen L. Michell, Ray Sheridan:
EMOCS: evolutionary multi-objective optimisation for clinical scorecard generation. GECCO 2019: 1174-1182 - [c40]Matthew Barrie Johns, Herman A. Mahmoud
, David J. Walker
, Nicholas D. F. Ross
, Edward C. Keedwell, Dragan A. Savic
:
Augmented evolutionary intelligence: combining human and evolutionary design for water distribution network optimisation. GECCO 2019: 1214-1222 - [c39]Nicholas D. F. Ross
, Matthew Barrie Johns, Edward C. Keedwell, Dragan A. Savic
:
Human-evolutionary problem solving through gamification of a bin-packing problem. GECCO (Companion) 2019: 1465-1473 - 2018
- [c38]Hojjat Rakhshani, Lhassane Idoumghar, Julien Lepagnot, Mathieu Brévilliers, Edward C. Keedwell:
Automatic hyperparameter selection in Autodock. BIBM 2018: 734-738 - [c37]Dennis G. Wilson, Silvio Rodrigues, Carlos Segura
, Ilya Loshchilov, Frank Hutter, Guillermo López Buenfil, Ahmed Kheiri
, Ed Keedwell, Mario Ocampo-Pineda, Ender Özcan
, Sergio Iwan Valdez Pea, Brian Goldman, Salvador Botello Rionda, Arturo Hernández Aguirre, Kalyan Veeramachaneni, Sylvain Cussat-Blanc:
Summary of evolutionary computation for wind farm layout optimization. GECCO (Companion) 2018: 31-32 - [c36]Ahamed Fayeez Tuani, Ed Keedwell, Matthew Collett:
Investigating Behavioural Diversity via Gaussian Heterogeneous Ant Colony Optimization for Combinatorial Optimization Problems. ICAAI 2018: 46-50 - [c35]Edward C. Keedwell, Mathieu Brévilliers, Lhassane Idoumghar, Julien Lepagnot, Hojjat Rakhshani:
A Novel Population Initialization Method Based on Support Vector Machine. SMC 2018: 751-756 - [i1]Hojjat Rakhshani, Lhassane Idoumghar, Julien Lepagnot, Mathieu Brévilliers, Edward C. Keedwell:
Automatic hyperparameter selection in Autodock. CoRR abs/1812.02618 (2018) - 2017
- [j16]Ahmed Kheiri
, Ed Keedwell:
A Hidden Markov Model Approach to the Problem of Heuristic Selection in Hyper-Heuristics with a Case Study in High School Timetabling Problems. Evol. Comput. 25(3): 473-501 (2017) - [c34]Ahamed Fayeez Tuani, Edward C. Keedwell, Matthew Collett:
H-ACO: A Heterogeneous Ant Colony Optimisation Approach with Application to the Travelling Salesman Problem. Artificial Evolution 2017: 144-161 - [c33]William B. Yates, Edward C. Keedwell:
Offline Learning for Selection Hyper-heuristics with Elman Networks. Artificial Evolution 2017: 217-230 - [c32]William B. Yates, Edward C. Keedwell:
Clustering of hyper-heuristic selections using the Smith-Waterman algorithm for offline learning. GECCO (Companion) 2017: 119-120 - 2016
- [j15]Michele Guidolin
, Albert S. Chen
, Bidur Ghimire, Edward C. Keedwell, Slobodan Djordjevic
, Dragan A. Savic
:
A weighted cellular automata 2D inundation model for rapid flood analysis. Environ. Model. Softw. 84: 378-394 (2016) - [c31]David J. Walker
, Ed Keedwell:
Multi-objective Optimisation with a Sequence-based Selection Hyper-heuristic. GECCO (Companion) 2016: 81-82 - [c30]David J. Walker
, Ed Keedwell:
Towards Many-Objective Optimisation with Hyper-heuristics: Identifying Good Heuristics with Indicators. PPSN 2016: 493-502 - 2015
- [j14]Emmanuel Sapin, Edward C. Keedwell, Timothy M. Frayling:
An Ant Colony Optimization and Tabu List Approach to the Detection of Gene-Gene Interactions in Genome-Wide Association Studies [Research Frontier]. IEEE Comput. Intell. Mag. 10(4): 54-65 (2015) - [j13]Kent McClymont, Ed Keedwell, Dragan A. Savic
:
An analysis of the interface between evolutionary algorithm operators and problem features for water resources problems. A case study in water distribution network design. Environ. Model. Softw. 69: 414-424 (2015) - [j12]Jonathan Mwaura, Ed Keedwell:
Evolving robot sub-behaviour modules using Gene Expression Programming. Genet. Program. Evolvable Mach. 16(2): 95-131 (2015) - [j11]Michael John Gibson, Edward C. Keedwell, Dragan A. Savic
:
An investigation of the efficient implementation of cellular automata on multi-core CPU and GPU hardware. J. Parallel Distributed Comput. 77: 11-25 (2015) - [c29]Ahmed Kheiri
, Ed Keedwell:
A Sequence-based Selection Hyper-heuristic Utilising a Hidden Markov Model. GECCO 2015: 417-424 - [c28]Edward C. Keedwell, Matthew Barrie Johns, Dragan A. Savic:
Spatial and Temporal Visualisation of Evolutionary Algorithm Decisions in Water Distribution Network Optimisation. GECCO (Companion) 2015: 941-948 - [c27]Jonathan Mwaura, Ed Keedwell:
Evolving Robotic Neuro-Controllers Using Gene Expression Programming. SSCI 2015: 1063-1072 - 2014
- [j10]Joe Townsend, Ed Keedwell, Antony Galton:
Artificial Development of Biologically Plausible Neural-Symbolic Networks. Cogn. Comput. 6(1): 18-34 (2014) - [j9]Holger R. Maier
, Zoran Kapelan, Joseph R. Kasprzyk
, Joshua B. Kollat, L. Shawn Matott, Maria C. Cunha
, Graeme C. Dandy, Matthew S. Gibbs
, Ed Keedwell, Angela Marchi, Avi Ostfeld
, Dragan A. Savic
, Dimitri P. Solomatine, Jasper A. Vrugt
, Aaron C. Zecchin
, Barbara S. Minsker
, E. J. Barbour, George Kuczera, F. Pasha, Andrea Castelletti
, Matteo Giuliani
, Patrick M. Reed
:
Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions. Environ. Model. Softw. 62: 271-299 (2014) - [j8]Emmanuel Sapin, Ed Keedwell:
A Subset-Based Ant Colony Optimisation with Tournament Path Selection for High-Dimensional Problems. Trans. Comput. Collect. Intell. 17: 232-247 (2014) - [c26]Ed Keedwell:
An analysis of the area under the ROC curve and its use as a metric for comparing clinical scorecards. BIBM 2014: 24-29 - [c25]Emmanuel Sapin, Ed Keedwell, Timothy M. Frayling:
Ant colony optimisation of decision trees for the detection of gene-gene interactions. BIBM 2014: 57-61 - [c24]Jonathan Mwaura, Ed Keedwell:
On using Gene Expression Programming to evolve multiple output robot controllers. ICES 2014: 173-180 - [c23]Ajit Narayanan, Edward C. Keedwell:
An evolutionary computational approach to phase and synchronization in biological circuits. ICNC 2014: 419-424 - 2013
- [j7]Ed Keedwell, Ajit Narayanan:
Gene expression rule discovery and multi-objective ROC analysis using a neural-genetic hybrid. Int. J. Data Min. Bioinform. 7(4): 376-396 (2013) - [c22]Joe Townsend, Ed Keedwell, Antony Galton:
Artificial development of connections in SHRUTI networks using a multi objective genetic algorithm. GECCO (Companion) 2013: 111-112 - [c21]Mike J. Gibson, Ed Keedwell, Dragan A. Savic
:
Understanding the efficient parallelisation of cellular automata on CPU and GPGPU hardware. GECCO (Companion) 2013: 171-172 - [c20]Emmanuel Sapin, Ed Keedwell, Timothy M. Frayling:
Subset-based ant colony optimisation for the discovery of gene-gene interactions in genome wide association studies. GECCO 2013: 295-302 - [c19]Matthew Barrie Johns, Edward C. Keedwell, Dragan A. Savic
:
Pipe smoothing genetic algorithm for least cost water distribution network design. GECCO 2013: 1309-1316 - [c18]Emmanuel Sapin, Ed Keedwell, Timothy M. Frayling:
Ant Colony Optimisation for Exploring Logical Gene-Gene Associations in Genome Wide Association Studies. IWBBIO 2013: 449-456 - 2012
- [j6]Kent McClymont, Ed Keedwell:
Deductive Sort and Climbing Sort: New Methods for Non-Dominated Sorting. Evol. Comput. 20(1): 1-26 (2012) - [c17]Ed Keedwell, Mark Morley
, Darren P. Croft
:
Continuous Trait-Based Particle Swarm Optimisation (CTB-PSO). ANTS 2012: 342-343 - [c16]Emmanuel Sapin, Ed Keedwell:
T-ACO Tournament Ant Colony Optimisation for High-dimensional Problems. IJCCI 2012: 81-86 - 2011
- [j5]Jacqueline Christmas
, Edward C. Keedwell, Timothy M. Frayling, John R. B. Perry:
Ant colony optimisation to identify genetic variant association with type 2 diabetes. Inf. Sci. 181(9): 1609-1622 (2011) - [c15]Kent McClymont, Ed Keedwell:
Benchmark multi-objective optimisation test problems with mixed encodings. IEEE Congress on Evolutionary Computation 2011: 2131-2138 - [c14]Kent McClymont, Edward C. Keedwell:
Markov chain hyper-heuristic (MCHH): an online selective hyper-heuristic for multi-objective continuous problems. GECCO 2011: 2003-2010 - [c13]Jonathan Mwaura, Ed Keedwell:
Evolving Modularity in Robot Behaviour Using Gene Expression Programming. TAROS 2011: 392-393 - 2010
- [c12]Ed Keedwell, Ajit Narayanan:
Gene expression rule discovery with a multi-objective neural-genetic hybrid. BIBM 2010: 649-656 - [c11]Kent McClymont, Ed Keedwell:
Optimising multi-modal polynomial mutation operators for multi-objective problem classes. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c10]Jonathan Mwaura, Ed Keedwell:
Evolution of robotic behaviours using Gene Expression Programming. IEEE Congress on Evolutionary Computation 2010: 1-8
2000 – 2009
- 2007
- [c9]Yufeng Guo, Ed Keedwell, Godfrey A. Walters, Soon-Thiam Khu:
Hybridizing Cellular Automata Principles and NSGAII for Multi-objective Design of Urban Water Networks. EMO 2007: 546-559 - [c8]Ed Keedwell, Ajit Narayanan:
Gene finding and rule discovery with a multi-objective neural-genetic hybrid. GECCO 2007: 428 - 2005
- [j4]Edward C. Keedwell, Soon-Thiam Khu:
A hybrid genetic algorithm for the design of water distribution networks. Eng. Appl. Artif. Intell. 18(4): 461-472 (2005) - [j3]Ed Keedwell, Ajit Narayanan:
Discovering Gene Networks with a Neural-Genetic Hybrid. IEEE ACM Trans. Comput. Biol. Bioinform. 2(3): 231-242 (2005) - [c7]Thorhildur Juliusdottir, David Corne, Ed Keedwell, Ajit Narayanan:
Two-Phase EA/k-NN for Feature Selection and Classification in Cancer Microarray Datasets. CIBCB 2005: 1-8 - [c6]A. Krishna, Ajit Narayanan, Ed Keedwell:
Neural Networks and Temporal Gene Expression Data. EvoWorkshops 2005: 64-73 - 2004
- [j2]Ajit Narayanan, Ed Keedwell, Jonas Gamalielsson, S. Tatineni:
Single-layer artificial neural networks for gene expression analysis. Neurocomputing 61: 217-240 (2004) - [c5]Ajit Narayanan, Evangelia Nana, Ed Keedwell:
Analyzing gene expression data for childhood medulloblastoma survival with artificial neural networks. CIBCB 2004: 9-16 - [c4]Ed Keedwell, Soon-Thiam Khu:
Hybrid Genetic Algorithms for Multi-Objective Optimisation of Water Distribution Networks. GECCO (2) 2004: 1042-1053 - 2003
- [b1]Edward C. Keedwell:
Knowledge discovery from gene expression data using neural-genetic models : a comparative study of four European countries with special attention to the education of these children. University of Exeter, Devon, UK, 2003 - [c3]Ed Keedwell, Ajit Narayanan:
Genetic Algorithms for Gene Expression Analysis. EvoWorkshops 2003: 76-86 - 2000
- [j1]Ed Keedwell, Ajit Narayanan, Dragan A. Savic:
Creating rules from trained networks using genetic algorithms. Int. J. Comput. Syst. Signals 1(1): 30-42 (2000) - [c2]Ed Keedwell, Ajit Narayanan, Dragan A. Savic:
Evolving rules from neural networks trained on continuous data. CEC 2000: 639-645 - [c1]Ed Keedwell, Florian Bessler, Ajit Narayanan, Dragan A. Savic
:
From data mining to rule refining A new tool for post data mining rule optimisation. ICTAI 2000: 82-85
Coauthor Index
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last updated on 2024-08-05 20:22 CEST by the dblp team
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