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Publications
- 2024
[j18]Truong Dang
, Tien Thanh Nguyen, John A. W. McCall, Eyad Elyan, Carlos Francisco Moreno-García:
Two-layer Ensemble of Deep Learning Models for Medical Image Segmentation. Cogn. Comput. 16(3): 1141-1160 (2024)- [j17]Jaume Bacardit, Alexander E. I. Brownlee, Stefano Cagnoni, Giovanni Iacca, John A. W. McCall, David J. Walker:
Introduction to the Special Issue on Explainable AI in Evolutionary Computation. ACM Trans. Evol. Learn. Optim. 4(1): 1:1-1:2 (2024) - [j16]Kate Han, Lee A. Christie, Alexandru-Ciprian Zavoianu, John A. W. McCall:
Exploring Representations for Optimizing Connected Autonomous Vehicle Routes in Multi-Modal Transport Networks Using Evolutionary Algorithms. IEEE Trans. Intell. Transp. Syst. 25(9): 10790-10801 (2024) - [c115]Truong Dang, Tien Thanh Nguyen, John McCall, Kate Han, Alan Wee-Chung Liew:
A Novel Surrogate Model for Variable-Length Encoding and its Application in Optimising Deep Learning Architecture. CEC 2024: 1-8 - [c114]Giancarlo Antonino Pasquale Ignazio Catalano, Alexander E. I. Brownlee, David E. Cairns, John A. W. McCall, Russell Ainslie:
Mining Potentially Explanatory Patterns via Partial Solutions. GECCO Companion 2024: 567-570 - [c113]Akinola Ogunsemi, John A. W. McCall, Alexandru-Ciprian Zavoianu, Lee A. Christie:
Cost and Performance Comparison of Holistic Solution Approaches for Complex Supply Chains on a Novel Linked Problem Benchmark. GECCO 2024 - [c112]Lee A. Christie, Atakan Sahin, Akinola Ogunsemi, Alexandru-Ciprian Zavoianu, John A. W. McCall:
On the Multi-objective Optimization of Wind Farm Cable Layouts with Regard to Cost and Robustness. PPSN (4) 2024: 367-382 - [i5]GianCarlo Catalano, Alexander E. I. Brownlee, David E. Cairns, John A. W. McCall, Russell Ainslie:
Mining Potentially Explanatory Patterns via Partial Solutions. CoRR abs/2404.04388 (2024) - [i4]Ryan Zhou, Jaume Bacardit, Alexander E. I. Brownlee, Stefano Cagnoni, Martin Fyvie, Giovanni Iacca, John A. W. McCall, Niki van Stein, David Walker, Ting Hu:
Evolutionary Computation and Explainable AI: A Roadmap to Transparent Intelligent Systems. CoRR abs/2406.07811 (2024) - 2023
- [j15]Daniel Dobos, Tien Thanh Nguyen, Truong Dang, Allan Wilson, Helen Corbett, John A. W. McCall, Phil Stockton:
A comparative study of anomaly detection methods for gross error detection problems. Comput. Chem. Eng. 175: 108263 (2023) - [j14]Anh Vu Luong, Tien Thanh Nguyen, Kate Han, Trung Hieu Vu, John McCall, Alan Wee-Chung Liew:
DEFEG: Deep Ensemble with Weighted Feature Generation. Knowl. Based Syst. 275: 110691 (2023) - [c111]Yijun Yan, Yinhe Li, Hanhe Lin, Md. Mostafa Kamal Sarker, Jinchang Ren, John McCall:
Underwater Object Detection for Smooth and Autonomous Operations of Naval Missions: A Pilot Dataset. BICS 2023: 113-122 - [c110]Martin Fyvie, John McCall, Lee A. Christie, Alexander E. I. Brownlee:
Explaining a Staff Rostering Genetic Algorithm using Sensitivity Analysis and Trajectory Analysis. GECCO Companion 2023: 1648-1656 - [c109]Martin Fyvie, John A. W. McCall, Lee A. Christie, Alexandru-Ciprian Zavoianu, Alexander E. I. Brownlee, Russell Ainslie:
Explaining a Staff Rostering Problem by Mining Trajectory Variance Structures. SGAI Conf. 2023: 275-290 - [c108]Joseph Collins, Alexandru-Ciprian Zavoianu, John A. W. McCall:
Comparison of Simulated Annealing and Evolution Strategies for Optimising Cyclical Rosters with Uneven Demand and Flexible Trainee Placement. SGAI Conf. 2023: 451-464 - [c107]Daniel Dobos, Truong Dang, Tien Thanh Nguyen, John McCall, Allan Wilson, Helen Corbett, Phil Stockton:
A Weighted Ensemble of Regression Methods for Gross Error Identification Problem. SSCI 2023: 413-420 - 2022
- [c106]Truong Dang, Anh Vu Luong, Alan Wee-Chung Liew, John McCall, Tien Thanh Nguyen:
Ensemble of deep learning models with surrogate-based optimization for medical image segmentation. CEC 2022: 1-8 - [c105]Alexandru-Ciprian Zavoianu, Benjamin Lacroix, John McCall:
Lightweight Interpolation-Based Surrogate Modelling for Multi-objective Continuous Optimisation. EUROCAST 2022: 53-60 - [c104]Kate Han, Lee A. Christie, Alexandru-Ciprian Zavoianu, John McCall:
On Discovering Optimal Trade-Offs When Introducing New Routes in Existing Multi-modal Public Transport Systems. EUROCAST 2022: 104-111 - [c103]Akinola Ogunsemi, John A. W. McCall, Mathias Kern, Benjamin Lacroix, David Corsar, Gilbert Owusu:
Facility location problem and permutation flow shop scheduling problem: a linked optimisation problem. GECCO Companion 2022: 735-738 - [c101]Akinola Ogunsemi, John McCall, Mathias Kern, Benjamin Lacroix, David Corsar, Gilbert Owusu:
Job Assignment Problem and Traveling Salesman Problem: A Linked Optimisation Problem. SGAI Conf. 2022: 19-33 - [c100]Truong Dang, Tien Thanh Nguyen, John McCall, Alan Wee-Chung Liew:
Ensemble Learning based on Classifier Prediction Confidence and Comprehensive Learning Particle Swarm Optimisation for Medical Image Segmentation. SSCI 2022: 269-276 - [i3]Alexander E. I. Brownlee, Martin Pelikan, John A. W. McCall, Andrei Petrovski:
An Application of a Multivariate Estimation of Distribution Algorithm to Cancer Chemotherapy. CoRR abs/2205.08438 (2022) - 2021
- [c99]Kate Han, Tien Pham, Trung Hieu Vu, Truong Dang, John A. W. McCall, Tien Thanh Nguyen:
VEGAS: A Variable Length-Based Genetic Algorithm for Ensemble Selection in Deep Ensemble Learning. ACIIDS 2021: 168-180 - [c98]Truong Dang, Tien Thanh Nguyen, Carlos Francisco Moreno-García, Eyad Elyan, John A. W. McCall:
Weighted Ensemble of Deep Learning Models based on Comprehensive Learning Particle Swarm Optimization for Medical Image Segmentation. CEC 2021: 744-751 - [c97]Daniel Dobos, Tien Thanh Nguyen, John A. W. McCall, Allan Wilson, Phil Stockton, Helen Corbett:
Weighted ensemble of gross error detection methods based on particle swarm optimization. GECCO Companion 2021: 307-308 - [c96]Kate Han, Lee A. Christie, Alexandru-Ciprian Zavoianu, John McCall:
Optimising the introduction of connected and autonomous vehicles in a public transport system using macro-level mobility simulations and evolutionary algorithms. GECCO Companion 2021: 315-316 - [c95]Arnaud Liefooghe, Sébastien Vérel, Benjamin Lacroix, Alexandru-Ciprian Zavoianu, John A. W. McCall:
Landscape features and automated algorithm selection for multi-objective interpolated continuous optimisation problems. GECCO 2021: 421-429 - [c93]Martin Fyvie, John A. W. McCall, Lee A. Christie:
Towards Explainable Metaheuristics: PCA for Trajectory Mining in Evolutionary Algorithms. SGAI Conf. 2021: 89-102 - [c92]Martin Fyvie, John A. W. McCall, Lee A. Christie:
Non-Deterministic Solvers and Explainable AI through Trajectory Mining. SICSA XAI 2021: 75-78 - [i2]Truong Dang, Tien Thanh Nguyen, John McCall, Eyad Elyan, Carlos Francisco Moreno-García:
Two layer Ensemble of Deep Learning Models for Medical Image Segmentation. CoRR abs/2104.04809 (2021) - [i1]Truong Dang, Tien Thanh Nguyen, John A. W. McCall, Alan Wee-Chung Liew:
Ensemble Learning based on Classifier Prediction Confidence and Comprehensive Learning Particle Swarm Optimisation for polyp localisation. CoRR abs/2104.04832 (2021) - 2020
- [j12]Christopher Brown, Vladimir Janjic, Mehdi Goli, John A. W. McCall:
Programming Heterogeneous Parallel Machines Using Refactoring and Monte-Carlo Tree Search. Int. J. Parallel Program. 48(4): 583-602 (2020) - [j11]Tien Thanh Nguyen, Manh Truong Dang, Vimal Anand Baghel, Anh Vu Luong, John McCall, Alan Wee-Chung Liew:
Evolving interval-based representation for multiple classifier fusion. Knowl. Based Syst. 201-202: 106034 (2020) - [j10]Tien Thanh Nguyen, Anh Vu Luong, Manh Truong Dang, Alan Wee-Chung Liew, John McCall:
Ensemble Selection based on Classifier Prediction Confidence. Pattern Recognit. 100: 107104 (2020) - [c91]Duc Thuan Do, Tien Thanh Nguyen, The Trung Nguyen, Anh Vu Luong, Alan Wee-Chung Liew, John McCall:
Confidence in Prediction: An Approach for Dynamic Weighted Ensemble. ACIIDS (1) 2020: 358-370 - [c90]Reginald Ankrah, Benjamin Lacroix, John A. W. McCall, Andrew Hardwick, Anthony Conway, Gilbert Owusu:
Racing Strategy for the Dynamic-Customer Location-Allocation Problem. CEC 2020: 1-8 - [c89]Ashish Upadhyay, Tien Thanh Nguyen, Stewart Massie, John A. W. McCall:
WEC: Weighted Ensemble of Text Classifiers. CEC 2020: 1-8 - [c88]Tien Thanh Nguyen, John McCall, Allan Wilson, Laud Ochei, Helen Corbett, Phil Stockton:
Evolved ensemble of detectors for gross error detection. GECCO Companion 2020: 281-282 - [c87]Tien Thanh Nguyen, Nang Van Pham, Manh Truong Dang, Anh Vu Luong, John McCall, Alan Wee-Chung Liew:
Multi-layer heterogeneous ensemble with classifier and feature selection. GECCO 2020: 725-733 - [c86]Anh Vu Luong, Trung Hieu Vu, Phuong Minh Nguyen, Nang Van Pham, John A. W. McCall, Alan Wee-Chung Liew, Tien Thanh Nguyen:
A Homogeneous-Heterogeneous Ensemble of Classifiers. ICONIP (5) 2020: 251-259 - [c85]Truong Dang, Tien Thanh Nguyen, John McCall:
Toward an Ensemble of Object Detectors. ICONIP (5) 2020: 458-467 - [c84]Alexandru-Ciprian Zavoianu, Benjamin Lacroix, John McCall:
Comparative Run-Time Performance of Evolutionary Algorithms on Multi-objective Interpolated Continuous Optimisation Problems. PPSN (1) 2020: 287-300 - [c83]Akinola Ogunsemi, John A. W. McCall, Mathias Kern, Benjamin Lacroix, David Corsar, Gilbert Owusu:
Ensemble-Based Relationship Discovery in Relational Databases. SGAI Conf. 2020: 286-300 - 2019
- [j9]Tien Thanh Nguyen, Manh Truong Dang, Dung Pham, Lan Phuong Dao, Anh Vu Luong, John McCall, Alan Wee-Chung Liew:
Deep Heterogeneous Ensemble. Aust. J. Intell. Inf. Process. Syst. 16(1): 1-9 (2019) - [j8]Tien Thanh Nguyen, Manh Truong Dang, Anh Vu Luong, Alan Wee-Chung Liew, Tiancai Liang, John McCall:
Multi-label classification via incremental clustering on an evolving data stream. Pattern Recognit. 95: 96-113 (2019) - [c82]Reginald Ankrah, Benjamin Lacroix, John A. W. McCall, Andrew Hardwick, Anthony Conway:
Introducing the Dynamic Customer Location-Allocation Problem. CEC 2019: 3157-3164 - [c81]Tien Thanh Nguyen, Anh Vu Luong, Thi Minh Van Nguyen, Trong Sy Ha, Alan Wee-Chung Liew, John McCall:
Simultaneous meta-data and meta-classifier selection in multiple classifier system. GECCO 2019: 39-46 - [c80]Benjamin Lacroix, John A. W. McCall:
Limitations of benchmark sets and landscape features for algorithm selection and performance prediction. GECCO (Companion) 2019: 261-262 - [c78]Tien Thanh Nguyen, Anh Vu Luong, Manh Truong Dang, Lan Phuong Dao, Thi Thu Thuy Nguyen, Alan Wee-Chung Liew, John McCall:
Evolving an Optimal Decision Template for Combining Classifiers. ICONIP (1) 2019: 608-620 - 2018
- [c77]Russell Ainslie, John A. W. McCall, Sid Shakya, Gilbert Owusu:
Tactical Plan Optimisation for Large Multi-Skilled Workforces Using a Bi-Level Model. CEC 2018: 1-8 - [c76]Reginald Ankrah, Olivier Regnier-Coudert, John A. W. McCall, Anthony Conway, Andrew Hardwick:
Performance Analysis of GA and PBIL Variants for Real-World Location-Allocation Problems. CEC 2018: 1-8 - [c75]Benjamin Lacroix, John A. W. McCall, Jérôme Lonchampt:
Iterated Racing Algorithm for Simulation-Optimisation of Maintenance Planning. CEC 2018: 1-7 - [c74]Charles Neau, Olivier Regnier-Coudert, John A. W. McCall:
An Analysis of Indirect Optimisation Strategies for Scheduling. CEC 2018: 1-8 - [c73]Reginald Ankrah, Benjamin Lacroix, John A. W. McCall, Andrew Hardwick, Anthony Conway:
A Holistic Metric Approach to Solving the Dynamic Location-Allocation Problem. SGAI Conf. 2018: 433-439 - 2017
- [c72]Mayowa Ayodele, John A. W. McCall, Olivier Regnier-Coudert:
Estimation of distribution algorithms for the Multi-Mode Resource Constrained Project scheduling problem. CEC 2017: 1579-1586 - [c71]Mayowa Ayodele, John A. W. McCall, Olivier Regnier-Coudert, Liam Bowie:
A Random Key based Estimation of Distribution Algorithm for the Permutation Flowshop Scheduling Problem. CEC 2017: 2364-2371 - [c70]Benjamin Lacroix, Lee A. Christie, John A. W. McCall:
Interpolated continuous optimisation problems with tunable landscape features. GECCO (Companion) 2017: 169-170 - [c69]Russell Ainslie, John A. W. McCall, Sid Shakya, Gilbert Owusu:
Predicting Service Levels Using Neural Networks. SGAI Conf. 2017: 411-416 - 2016
- [c68]Mayowa Ayodele, John A. W. McCall, Olivier Regnier-Coudert:
BPGA-EDA for the multi-mode resource constrained project scheduling problem. CEC 2016: 3417-3424 - [c66]Russell Ainslie, John A. W. McCall, Siddhartha Shakya, Gilbert Owusu:
Predictive planning with neural networks. IJCNN 2016: 2110-2117 - [c65]Mayowa Ayodele, John A. W. McCall, Olivier Regnier-Coudert:
RK-EDA: A Novel Random Key Based Estimation of Distribution Algorithm. PPSN 2016: 849-858 - 2015
- [c64]Prapa Rattadilok, John A. W. McCall, Trevor Burbridge, Andrea Soppera, Philip Eardley:
A data fusion framework for large-scale measurement platforms. IEEE BigData 2015: 2150-2158 - [c63]Alexander E. I. Brownlee, John A. W. McCall, Lee A. Christie:
Structural coherence of problem and algorithm: An analysis for EDAs on all 2-bit and 3-bit problems. CEC 2015: 2066-2073 - [c62]Juan Ignacio Alonso-Barba, Luis de la Ossa, Olivier Regnier-Coudert, John A. W. McCall, José A. Gámez, José Miguel Puerta:
Ant Colony and Surrogate Tree-Structured Models for Orderings-Based Bayesian Network Learning. GECCO 2015: 543-550 - [c61]Mayowa Ayodele, John A. W. McCall, Olivier Regnier-Coudert:
Probabilistic Model Enhanced Genetic Algorithm for Multi-Mode Resource Constrained Project Scheduling Problem. GECCO (Companion) 2015: 745-746 - [c60]John A. W. McCall, Lee A. Christie, Alexander E. I. Brownlee:
Generating Easy and Hard Problems using the Proximate Optimality Principle. GECCO (Companion) 2015: 767-768 - [c59]Russell Ainslie, Siddhartha Shakya, John A. W. McCall, Gilbert Owusu:
Optimising Skill Matching in the Service Industry for Large Multi-skilled Workforces. SGAI Conf. 2015: 231-243 - 2014
- [j6]Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
D2MOPSO: MOPSO Based on Decomposition and Dominance with Archiving Using Crowding Distance in Objective and Solution Spaces. Evol. Comput. 22(1): 47-77 (2014) - [c58]Lee A. Christie, John A. W. McCall, David P. Lonie:
Minimal walsh structure and ordinal linkage of monotonicity-invariant function classes on bit strings. GECCO 2014: 333-340 - [c57]Olivier Regnier-Coudert, John A. W. McCall:
Factoradic Representation for Permutation Optimisation. PPSN 2014: 332-341 - 2013
- [j4]Alexander E. I. Brownlee, Olivier Regnier-Coudert, John A. W. McCall, Stewart Massie, Stefan Stulajter:
An application of a GA with Markov network surrogate to feature selection. Int. J. Syst. Sci. 44(11): 2039-2056 (2013) - [j3]Alexander E. I. Brownlee, John A. W. McCall, Qingfu Zhang:
Fitness Modeling With Markov Networks. IEEE Trans. Evol. Comput. 17(6): 862-879 (2013) - [c55]Mehdi Goli, John A. W. McCall, Christopher Brown, Vladimir Janjic, Kevin Hammond:
Mapping parallel programs to heterogeneous CPU/GPU architectures using a Monte Carlo Tree Search. IEEE Congress on Evolutionary Computation 2013: 2932-2939 - [c53]Olivier Regnier-Coudert, John A. W. McCall, Mayowa Ayodele:
Geometric-based sampling for permutation optimization. GECCO 2013: 399-406 - [c52]Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
Mutual Information for Performance Assessment of Multi Objective Optimisers: Preliminary Results. IDEAL 2013: 537-544 - [c50]Lee A. Christie, David P. Lonie, John A. W. McCall:
Partial structure learning by subset walsh transform. UKCI 2013: 128-135 - [p1]Thierry Mamer, John A. W. McCall, Siddhartha Shakya, Gilbert Owusu, Olivier Regnier-Coudert:
Understanding Team Dynamics with Agent-Based Simulation. Transforming Field and Service Operations 2013: 183-198 - [e1]Gilbert Owusu, Paul O'Brien, John A. W. McCall, Neil F. Doherty:
Transforming Field and Service Operations, Methodologies for Successful Technology-Driven Business Transformation. Springer 2013, ISBN 978-3-642-44969-7 [contents] - 2012
- [j2]Olivier Regnier-Coudert, John A. W. McCall, Robert Lothian, Thomas Lam, Sam McClinton, James N'Dow:
Machine learning for improved pathological staging of prostate cancer: A performance comparison on a range of classifiers. Artif. Intell. Medicine 55(1): 25-35 (2012) - [c49]Noura Al Moubayed, Bashar Awwad Shiekh Hasan, John Q. Gan, Andrei Petrovski, John A. W. McCall:
Continuous presentation for multi-objective channel selection in Brain-Computer Interfaces. IEEE Congress on Evolutionary Computation 2012: 1-7 - [c48]Olivier Regnier-Coudert, John A. W. McCall:
An Island Model Genetic Algorithm for Bayesian network structure learning. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c47]Yanghui Wu, John A. W. McCall, David Corne, Olivier Regnier-Coudert:
Landscape analysis for hyperheuristic Bayesian Network structure learning on unseen problems. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c46]Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
D 2 MOPSO: Multi-Objective Particle Swarm Optimizer Based on Decomposition and Dominance. EvoCOP 2012: 75-86 - [c45]Alexander E. I. Brownlee, John A. W. McCall, Martin Pelikan:
Influence of selection on structure learning in markov network EDAs: an empirical study. GECCO 2012: 249-256 - [c42]Olivier Regnier-Coudert, John A. W. McCall:
Competing Mutating Agents for Bayesian Network Structure Learning. PPSN (1) 2012: 216-225 - 2011
- [c41]Yanghui Wu, John A. W. McCall, David Corne:
Fitness landscape analysis of Bayesian network structure learning. IEEE Congress on Evolutionary Computation 2011: 981-988 - [c40]Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
Multi-objective optimisation of cancer chemotherapy using smart PSO with decomposition. MCDM 2011: 81-88 - [c39]Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
Clustering based leaders' selection in multi-objective evolutionary algorithms. GECCO (Companion) 2011: 95-96 - [c38]Olivier Regnier-Coudert, John A. W. McCall:
Privacy-preserving approach to bayesian network structure learning from distributed data. GECCO (Companion) 2011: 815-816 - [c37]Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
Clustering-Based Leaders' Selection in Multi-Objective Particle Swarm Optimisation. IDEAL 2011: 100-107 - [c36]Thierry Mamer, Siddhartha Shakya, John A. W. McCall, Gilbert Owusu:
Intelligent Tuning of a Dynamic Business Simulation Environment. SGAI Conf. 2011: 355-368 - 2010
- [c35]Robert Barbour, David W. Corne, John A. W. McCall:
Accelerated optimisation of chemotherapy dose schedules using fitness inheritance. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c34]Alexander E. I. Brownlee, Olivier Regnier-Coudert, John A. W. McCall, Stewart Massie:
Using a Markov network as a surrogate fitness function in a genetic algorithm. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c33]François A. Fournier, John A. W. McCall, Andrei Petrovski, Peter J. Barclay:
Evolved Bayesian Network models of rig operations in the gulf of Mexico. IEEE Congress on Evolutionary Computation 2010: 1-7 - [c32]Jean-Claude Golovine, John A. W. McCall, Patrik O'Brian Holt:
Evolving interface designs to minimize user task times as simulated in a cognitive architecture. IEEE Congress on Evolutionary Computation 2010: 1-7 - [c31]Yanghui Wu, John A. W. McCall, David W. Corne:
Two novel Ant Colony Optimization approaches for Bayesian network structure learning. IEEE Congress on Evolutionary Computation 2010: 1-7 - [c30]Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
A Novel Smart Multi-Objective Particle Swarm Optimisation Using Decomposition. PPSN (2) 2010: 1-10 - [c29]Yanghui Wu, John A. W. McCall, David Corne:
Comparative Analysis of Search and Score Metaheuristics for Bayesian Network Structure Learning Using Node Juxtaposition Distributions. PPSN (1) 2010: 424-433 - 2009
- [c28]Alexander E. I. Brownlee, John A. W. McCall, Siddhartha Shakya, Qingfu Zhang:
Structure learning and optimisation in a Markov-network based estimation of distribution algorithm. IEEE Congress on Evolutionary Computation 2009: 447-454 - [c27]Siddhartha Shakya, Alexander E. I. Brownlee, John A. W. McCall, François A. Fournier, Gilbert Owusu:
A fully multivariate DEUM algorithm. IEEE Congress on Evolutionary Computation 2009: 479-486 - 2008
- [c26]Paul Michael Godley, Julie Cowie, David E. Cairns, John A. W. McCall, C. Howie:
Optimisation of cancer chemotherapy schedules using directed intervention crossover approaches. IEEE Congress on Evolutionary Computation 2008: 2532-2537 - [c25]Alexander E. I. Brownlee, John A. W. McCall, Qingfu Zhang, Deryck Forsyth Brown:
Approaches to selection and their effect on fitness modelling in an Estimation of Distribution Algorithm. IEEE Congress on Evolutionary Computation 2008: 2621-2628 - [c24]Yanghui Wu, John A. W. McCall, Paul Michael Godley, Alexander E. I. Brownlee, David E. Cairns, Julie Cowie:
Bio-control in mushroom farming using a Markov network EDA. IEEE Congress on Evolutionary Computation 2008: 2991-2996 - [c23]Paul Michael Godley, David E. Cairns, Julie Cowie, John A. W. McCall:
Fitness directed intervention crossover approaches applied to bio-scheduling problems. CIBCB 2008: 120-127 - [c21]Alexander E. I. Brownlee, Martin Pelikan, John A. W. McCall, Andrei Petrovski:
An application of a multivariate estimation of distribution algorithm to cancer chemotherapy. GECCO 2008: 463-464 - [c20]Alexander E. I. Brownlee, Yanghui Wu, John A. W. McCall, Paul Michael Godley, David E. Cairns, Julie Cowie:
Optimisation and fitness modelling of bio-control in mushroom farming using a Markov network eda. GECCO 2008: 465-466 - [c19]Paul Michael Godley, David E. Cairns, Julie Cowie, Kevin Swingler, John A. W. McCall:
The effects of mutation and directed intervention crossover when applied to scheduling chemotherapy. GECCO 2008: 1105-1106 - [c17]Thierry Mamer, Christopher H. Bryant, John A. W. McCall:
L-Modified ILP Evaluation Functions for Positive-Only Biological Grammar Learning. ILP 2008: 176-191 - 2007
- [j1]Siddhartha Shakya, John A. W. McCall:
Optimization by estimation of distribution with DEUM framework based on Markov random fields. Int. J. Autom. Comput. 4(3): 262-272 (2007) - [c15]Alexander E. I. Brownlee, John A. W. McCall, Deryck Forsyth Brown:
Solving the MAXSAT problem using a multivariate EDA based on Markov networks. GECCO (Companion) 2007: 2423-2428 - 2006
- [c14]Siddhartha Shakya, John A. W. McCall, Deryck Forsyth Brown:
Solving the Ising Spin Glass Problem using a Bivariate EDA based on Markov Random Fields. IEEE Congress on Evolutionary Computation 2006: 908-915 - [c13]Andrei Petrovski, Siddhartha Shakya, John A. W. McCall:
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms. GECCO 2006: 413-418 - 2005
- [c12]Andrei Petrovski, Alexander E. I. Brownlee, John A. W. McCall:
Statistical optimisation and tuning of GA factors. Congress on Evolutionary Computation 2005: 758-764 - [c11]Siddhartha Shakya, John A. W. McCall, Deryck Forsyth Brown:
Incorporating a Metropolis method in a distribution estimation using Markov random field algorithm. Congress on Evolutionary Computation 2005: 2576-2583 - [c10]Andrei Petrovski, John A. W. McCall:
Smart problem solving environment for medical decision support. GECCO Workshops 2005: 152-158 - [c9]Siddhartha Shakya, John A. W. McCall, Deryck Forsyth Brown:
Using a Markov network model in a univariate EDA: an empirical cost-benefit analysis. GECCO 2005: 727-734 - 2004
- [c8]Andrei Petrovski, Bhavani Sudha, John A. W. McCall:
Optimising Cancer Chemotherapy Using Particle Swarm Optimisation and Genetic Algorithms. PPSN 2004: 633-641 - 2001
- [c6]Deryck Forsyth Brown, A. Beatriz Garmendia-Doval, John A. W. McCall:
Markov Random Field Modelling of Royal Road Genetic Algorithms. Artificial Evolution 2001: 65-76 - [c5]Andrei Petrovski, John A. W. McCall:
Multi-objective Optimisation of Cancer Chemotherapy Using Evolutionary Algorithms. EMO 2001: 531-545 - 2000
- [c4]Deryck Forsyth Brown, S. J. Cuddy, A. Beatriz Garmendia-Doval, John A. W. McCall:
The Prediction of Permeability in Oil-Bearing Strata using Genetic Algorithms. Artificial Intelligence and Soft Computing 2000: 53-57 - [c2]Deryck Forsyth Brown, A. Beatriz Garmendia-Doval, John A. W. McCall:
A functional framework for the implementation of genetic algorithms: Comparing Haskell and Standard ML. Scottish Functional Programming Workshop 2000: 27-38
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last updated on 2024-09-19 00:30 CEST by the dblp team
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