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2020 – today
- 2024
[j35]Kyle W. Pretorius, Nelishia Pillay:
Neural network crossover in genetic algorithms using genetic programming. Genet. Program. Evolvable Mach. 25(1): 7 (2024)- [j34]Rahul Kapoor, Nelishia Pillay:
A genetic programming approach to the automated design of CNN models for image classification and video shorts creation. Genet. Program. Evolvable Mach. 25(1): 10 (2024) - [j33]Jose M. Tapia-Avitia, Jorge M. Cruz-Duarte
, Iván Amaya, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Nelishia Pillay:
Analysing hyper-heuristics based on Neural Networks for the automatic design of population-based metaheuristics in continuous optimisation problems. Swarm Evol. Comput. 89: 101616 (2024) - [c92]Mia Gerber, Nelishia Pillay:
Dynamic Algorithm Composition for Image Segmentation. CEC 2024: 1-8 - [c91]Mia Gerber, Nelishia Pillay:
Dynamic Function Generation for Text Classification. CEC 2024: 1-8 - [c90]Guillermo Pérez-Espinosa, Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Nelishia Pillay:
Tailoring Metaheuristics for Designing Thermodynamic-Optimal Cooling Devices for Microelectronic Thermal Management Applications. CEC 2024: 1-8 - [c89]Weiyao Meng, Rong Qu, Nelishia Pillay:
Machine Learning for Evolutionary Computation - the Vehicle Routing Problems Competition. GECCO Companion 2024: 13-14 - [c88]Nelishia Pillay:
Transfer Learning in Evolutionary Spaces. GECCO Companion 2024: 1005-1016 - [c87]Mia Gerber, Nelishia Pillay:
Dynamic Neural Architecture Search for Image Classification. GECCO Companion 2024: 1554-1562 - 2023
- [c86]Emilio Singh, Nelishia Pillay:
A Study of Ant-Based Pheromone Spaces for Generation Perturbative Hyper-Heuristics. GECCO 2023: 84-92 - [c85]Mia Gerber, Nelishia Pillay:
Automated algorithm composition of unsupervised image clustering algorithms. GECCO Companion 2023: 467-470 - [c84]Mia Gerber, Nelishia Pillay:
An analysis of choice functions for Fuzzy ART using grammatical evolution. GECCO Companion 2023: 571-574 - [c83]Rahul Kapoor, Nelishia Pillay:
Iterative Structure-Based Genetic Programming for Neural Architecture Search. GECCO Companion 2023: 595-598 - [c82]Jeffrey Russell, Nelishia Pillay:
A Selection Hyper-Heuristic for Transfer Learning in Genetic Programming. GECCO Companion 2023: 631-634 - [c81]Nelishia Pillay:
Transfer Learning in Evolutionary Spaces. GECCO Companion 2023: 1037-1047 - 2022
- [j32]Cry Kuranga, Nelishia Pillay:
A comparative study of nonlinear regression and autoregressive techniques in hybrid with particle swarm optimization for time-series forecasting. Expert Syst. Appl. 190: 116163 (2022) - [j31]Jared O'Reilly, Nelishia Pillay:
Supplementary-architecture weight-optimization neural networks. Neural Comput. Appl. 34(13): 11177-11197 (2022) - [j30]Emilio Singh, Nelishia Pillay:
A study of ant-based pheromone spaces for generation constructive hyper-heuristics. Swarm Evol. Comput. 72: 101095 (2022) - [c80]Tapotosh Ghosh, Md. Hasan Al Banna, M. Jaber Al Nahian, M. Shamim Kaiser, Mufti Mahmud, Shaobao Li, Nelishia Pillay:
A Privacy-Preserving Federated-MobileNet for Facial Expression Detection from Images. AII 2022: 277-292 - [c79]Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Nelishia Pillay:
A Transfer Learning Hyper-heuristic Approach for Automatic Tailoring of Unfolded Population-based Metaheuristics. CEC 2022: 1-8 - [c78]Ahmed Hassan, Nelishia Pillay:
Automated Design of Hybrid Metaheuristics: A Fitness Landscape Analysis. CEC 2022: 1-8 - [c77]Ahmed Hassan, Nelishia Pillay:
Hybridizing A Genetic Algorithm With Reinforcement Learning for Automated Design of Genetic Algorithms. CEC 2022: 1-8 - [c76]Ying Ying Liu, Parimala Thulasiraman, Nelishia Pillay:
Bicriterion Coevolution for the Multi-objective Travelling Salesperson Problem. CEC 2022: 1-8 - [c75]Emilio Singh, Nelishia Pillay:
A Study of Transfer Learning in an Ant-Based Generation Construction Hyper-Heuristic. CEC 2022: 1-7 - [c74]Jose M. Tapia-Avitia, Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Nelishia Pillay:
A Primary Study on Hyper-Heuristics Powered by Artificial Neural Networks for Customising Population-based Metaheuristics in Continuous Optimisation Problems. CEC 2022: 1-8 - [c73]Nelishia Pillay:
Transfer learning in evolutionary spaces. GECCO Companion 2022: 1038-1045 - [c72]Derrick Beckedahl, Nelishia Pillay:
Bi-Space Search: Optimizing the Hybridization of Search Spaces in Solving the One Dimensional Bin Packing Problem. ICAISC (2) 2022: 206-217 - [c71]Ahmed Hassan, Nelishia Pillay:
Automated Design of Dynamic Heuristic Set Selection for Cross-Domain Selection Hyper-Heuristics. ICAISC (1) 2022: 219-229 - [c70]Christopher Rajah, Nelishia Pillay:
An Improved Structure-Based Partial Solution Search for the Examination Timetabling Problem. ICAISC (2) 2022: 314-326 - [c69]Cry Kuranga, Nelishia Pillay:
A Comparative Study of Genetic Programming Variants. ICAISC (1) 2022: 377-386 - [c68]Mia Gerber, Nelishia Pillay:
Automated design of feature extraction for unsupervised image clustering using grammatical evolution. SSCI 2022: 30-37 - [c67]Jared O'Reilly, Nelishia Pillay:
Supplementary-architecture weight-optimization neural networks for advanced weight optimizers. SSCI 2022: 47-54 - [c66]Emilio Singh, Nelishia Pillay:
A Parameter-Based Analysis of Ant-Based Generation Hyper-Heuristics. SSCI 2022: 812-819 - [c65]Ying Ying Liu, Parimala Thulasiraman, Nelishia Pillay:
Worst and Generalized Severity Evaluation for Evolutionary Dynamic Multi-objective Optimization. SSCI 2022: 1012-1020 - 2021
- [j29]George Mweshi, Nelishia Pillay:
An improved grammatical evolution approach for generating perturbative heuristics to solve combinatorial optimization problems. Expert Syst. Appl. 165: 113853 (2021) - [j28]Cry Kuranga, Nelishia Pillay:
Genetic programming-based regression for temporal data. Genet. Program. Evolvable Mach. 22(3): 297-324 (2021) - [j27]Nelishia Pillay, Rong Qu:
Assessing hyper-heuristic performance. J. Oper. Res. Soc. 72(11): 2503-2516 (2021) - [j26]Hugo Jair Escalante, Quanming Yao, Wei-Wei Tu, Nelishia Pillay, Rong Qu, Yang Yu, Neil Houlsby:
Guest Editorial: Automated Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. 43(9): 2887-2890 (2021) - [c64]Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Nelishia Pillay:
Automated Design of Unfolded Metaheuristics and the Effect of Population Size. CEC 2021: 1155-1162 - [c63]Nelishia Pillay, Mia Gerber, Katerina Holan, Steven A. Whitham, Dave K. Berger:
Quantifying the Severity of Common Rust in Maize Using Mask R-CNN. ICAISC (1) 2021: 202-213 - [c62]Emilio Singh, Nelishia Pillay:
Ant-Based Hyper-Heuristics for the Movie Scene Scheduling Problem. ICAISC (2) 2021: 342-353 - [c61]Luveshan Marimuthu, Nelishia Pillay, Rivak Punchoo, Sachin Bhoora:
A Comparison of Machine Learning Techniques for Diagnosing Multiple Myeloma. ICAISC (2) 2021: 483-494 - [c60]Mia Gerber, Nelishia Pillay, Katerina Holan, Steven A. Whitham, Dave K. Berger:
Automated Hyper-Parameter Tuning of a Mask R-CNN for Quantifying Common Rust Severity in Maize. IJCNN 2021: 1-7 - [c59]Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Nelishia Pillay:
Naïve Hyper-heuristic Online Learning to Generate Unfolded Population-based Metaheuristics to Solve Continuous Optimization Problems. SSCI 2021: 1-8 - [c58]Mia Gerber, Nelishia Pillay, Razia Khammissa:
A Comparative Study of Supervised and Unsupervised Neural Networks for Oral Lesion Detection. SSCI 2021: 1-7 - [c57]Ahmed Hassan, Nelishia Pillay:
An Investigation of Automated Design of VMAF. SSCI 2021: 1-8 - [c56]Kyle W. Pretorius, Nelishia Pillay:
Population based Reinforcement Learning. SSCI 2021: 1-8 - [c55]Darius Scheepers, Nelishia Pillay:
A Study of Transfer Learning in a Generation Constructive Hyper-Heuristic for One Dimensional Bin Packing. SSCI 2021: 1-7 - [c54]Ahmed Hassan, Nelishia Pillay:
Dynamic Heuristic Set Selection for Cross-Domain Selection Hyper-heuristics. TPNC 2021: 33-44 - [c53]Thambo Nyathi, Nelishia Pillay:
On the Transfer Learning of Genetic Programming Classification Algorithms. TPNC 2021: 47-58 - [c52]Emilio Singh, Nelishia Pillay:
Ant-Based Generation Constructive Hyper-heuristics for the Movie Scene Scheduling Problem. TPNC 2021: 109-120 - [p2]Nelishia Pillay, Thambo Nyathi:
Automated Design of Classification Algorithms. Automated Design of Machine Learning and Search Algorithms 2021: 171-184 - [p1]Nelishia Pillay:
Automated Design (AutoDes): Current Trends and Future Research Directions. Automated Design of Machine Learning and Search Algorithms 2021: 185-187 - [e2]Nelishia Pillay, Rong Qu:
Automated Design of Machine Learning and Search Algorithms. Natural Computing Series, Springer 2021, ISBN 978-3-030-72068-1 [contents] - 2020
- [j25]Rong Qu, Graham Kendall, Nelishia Pillay:
The General Combinatorial Optimization Problem: Towards Automated Algorithm Design. IEEE Comput. Intell. Mag. 15(2): 14-23 (2020) - [j24]Nelishia Pillay:
The impact of genetic programming in education. Genet. Program. Evolvable Mach. 21(1-2): 87-97 (2020) - [c51]Derrick Beckedahl, Nelishia Pillay:
A Study of Bi-space Search for Solving the One-Dimensional Bin Packing Problem. ICAISC (2) 2020: 277-289 - [c50]Kyle Pretorious, Nelishia Pillay:
A Comparative Study of Classifiers for Thumbnail Selection. IJCNN 2020: 1-7 - [c49]Cry Kuranga, Nelishia Pillay:
Nonlinear Regression in Dynamic Environments Using Particle Swarm Optimization. TPNC 2020: 133-144
2010 – 2019
- 2019
- [j23]Nelishia Pillay, Ender Özcan:
Automated generation of constructive ordering heuristics for educational timetabling. Ann. Oper. Res. 275(1): 181-208 (2019) - [j22]Ahmed Hassan, Nelishia Pillay:
Hybrid metaheuristics: An automated approach. Expert Syst. Appl. 130: 132-144 (2019) - [c48]Christopher Rajah, Nelishia Pillay:
A Structure-Based Partial Solution Search for the Examination Timetabling Problem. CEC 2019: 81-86 - [c47]George Mweshi, Nelishia Pillay:
A Grammatical Evolution Approach for the Automated Generation of Perturbative Heuristics. CEC 2019: 2642-2648 - 2018
- [b1]Nelishia Pillay, Rong Qu:
Hyper-Heuristics: Theory and Applications. Natural Computing Series, Springer 2018, ISBN 978-3-319-96513-0, pp. 3-101 - [j21]Nelishia Pillay, Rong Qu, Dipti Srinivasan, Barbara Hammer, Kenneth Sörensen:
Automated Design of Machine Learning and Search Algorithms [Guest Editorial]. IEEE Comput. Intell. Mag. 13(2): 16-17 (2018) - [j20]Anisa W. Ragalo, Nelishia Pillay:
An investigation of dynamic fitness measures for genetic programming. Expert Syst. Appl. 92: 52-72 (2018) - [j19]Thambo Nyathi, Nelishia Pillay:
Comparison of a genetic algorithm to grammatical evolution for automated design of genetic programming classification algorithms. Expert Syst. Appl. 104: 213-234 (2018) - [j18]Anisa W. Ragalo, Nelishia Pillay:
Evolving dynamic fitness measures for genetic programming. Expert Syst. Appl. 109: 162-187 (2018) - [c46]Ahmed Hassan, Nelishia Pillay:
An Improved Meta-Genetic Algorithm for Hybridizing Metaheuristics. CEC 2018: 1-8 - [c45]Derrick Beckedahl, Andreas Nel, Nelishia Pillay:
A Study of Multi-space Search Optimization. ISDA (1) 2018: 1-9 - [c44]Gisele Lobo Pappa, Michael T. M. Emmerich, Ana L. C. Bazzan, Will N. Browne, Kalyanmoy Deb, Carola Doerr, Marko Durasevic, Michael G. Epitropakis, Saemundur O. Haraldsson, Domagoj Jakobovic, Pascal Kerschke, Krzysztof Krawiec, Per Kristian Lehre, Xiaodong Li, Andrei Lissovoi, Pekka Malo, Luis Martí, Yi Mei, Juan Julián Merelo Guervós, Julian F. Miller, Alberto Moraglio, Antonio J. Nebro, Su Nguyen, Gabriela Ochoa, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Marc Schoenauer, Roman Senkerik, Ankur Sinha, Ofer M. Shir, Dirk Sudholt, L. Darrell Whitley, Mark Wineberg, John R. Woodward, Mengjie Zhang:
Tutorials at PPSN 2018. PPSN (2) 2018: 477-489 - [c43]Thambo Nyathi, Nelishia Pillay:
Automated Design of Genetic Programming Classification Algorithms for Financial Forecasting Using Evolutionary Algorithms. TPNC 2018: 201-214 - [r1]Marc Sevaux, Kenneth Sörensen, Nelishia Pillay:
Adaptive and Multilevel Metaheuristics. Handbook of Heuristics 2018: 3-21 - 2017
- [c42]Nelishia Pillay, Derrick Beckedahl:
EvoHyp - a Java toolkit for evolutionary algorithm hyper-heuristics. CEC 2017: 2706-2713 - [c41]Ahmed Hassan, Nelishia Pillay:
A Meta-Genetic Algorithm for Hybridizing Metaheuristics. EPIA 2017: 369-381 - [c40]Thambo Nyathi, Nelishia Pillay:
Automated Design of Genetic Programming Classification Algorithms Using a Genetic Algorithm. EvoApplications (2) 2017: 224-239 - 2016
- [j17]Nelishia Pillay:
A review of hyper-heuristics for educational timetabling. Ann. Oper. Res. 239(1): 3-38 (2016) - [j16]Nelishia Pillay:
Incorporating chaos into the developmental approach for solving the examination timetabling problem. Int. J. Bio Inspired Comput. 8(6): 355-366 (2016) - [c39]Nelishia Pillay:
Evolving construction heuristics for the curriculum based university course timetabling problem. CEC 2016: 4437-4443 - [c38]Carola Doerr, Nicolas Bredèche, Enrique Alba, Thomas Bartz-Beielstein, Dimo Brockhoff, Benjamin Doerr, Gusz Eiben, Michael G. Epitropakis, Carlos M. Fonseca, Andreia P. Guerreiro, Evert Haasdijk, Jacqueline Heinerman, Julien Hubert, Per Kristian Lehre, Luigi Malagò, Juan Julián Merelo Guervós, Julian Francis Miller, Boris Naujoks, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Patricia Ryser-Welch, Giovanni Squillero, Jörg Stork, Dirk Sudholt, Alberto Paolo Tonda, L. Darrell Whitley, Martin Zaefferer:
Tutorials at PPSN 2016. PPSN 2016: 1012-1022 - [c37]Nomzamo Ntombela, Nelishia Pillay:
Evolving Construction Heuristics for the Symmetric Travelling Salesman Problem. SAICSIT 2016: 30:1-30:5 - [e1]Nelishia Pillay, Andries P. Engelbrecht, Ajith Abraham, Mathys C. du Plessis, Václav Snásel, Azah Kamilah Muda:
Advances in Nature and Biologically Inspired Computing - Proceedings of the 7th World Congress on Nature and Biologically Inspired Computing (NaBIC 2015) in Pietermaritzburg, South Africa, held December 01-03, 2015. Advances in Intelligent Systems and Computing 419, Springer 2016, ISBN 978-3-319-27399-0 [contents] - 2015
- [j15]Nelishia Pillay:
Intelligent System Design Using Hyper-Heuristics. South Afr. Comput. J. 56 (2015) - [c36]Clive Frankland, Nelishia Pillay:
Evolving game playing strategies for Othello. CEC 2015: 1498-1504 - [c35]Christopher Rajah, Nelishia Pillay:
Combining Development and Evolution. IJCCI (ECTA) 2015: 188-195 - [c34]Kevin Igwe, Nelishia Pillay:
A Study of Genetic Programming and Grammatical Evolution for Automatic Object-Oriented Programming: A Focus on the List Data Structure. NaBIC 2015: 151-163 - [c33]Clive Frankland, Nelishia Pillay:
Evolving Heuristic Based Game Playing Strategies for Checkers Incorporating Reinforcement Learning. NaBIC 2015: 165-178 - [c32]Ahmed Hassan, Nelishia Pillay:
A Hyper-Heuristic Approach to Solving the Ski-Lodge Problem. NaBIC 2015: 201-210 - [c31]Nelishia Pillay:
A Generative Hyper-Heuristic for Deriving Heuristics for Classical Artificial Intelligence Problems. NaBIC 2015: 337-346 - [c30]Clive Frankland, Nelishia Pillay:
Evolving Game Playing Strategies for Othello Incorporating Reinforcement Learning and Mobility. SAICSIT 2015: 16:1-16:9 - 2014
- [j14]Nelishia Pillay:
A survey of school timetabling research. Ann. Oper. Res. 218(1): 261-293 (2014) - [j13]Gerhard Post, Jeffrey H. Kingston, Samad Ahmadi, Sophia Daskalaki, Christos Gogos, Jari Kyngäs, Cimmo Nurmi, Nysret Musliu, Nelishia Pillay, Haroldo G. Santos, Andrea Schaerf:
XHSTT: an XML archive for high school timetabling problems in different countries. Ann. Oper. Res. 218(1): 295-301 (2014) - [c29]Anisa W. Ragalo, Nelishia Pillay:
A Hyper-heuristic approach towards mitigating Premature Convergence caused by the objective fitness function in GP. ISDA 2014: 68-75 - [c28]Emmanuel Dufourq, Nelishia Pillay:
Hybridizing evolutionary algorithms for creating classifier ensembles. NaBIC 2014: 84-90 - 2013
- [j12]Anisa W. Ragalo, Nelishia Pillay:
Improved evolvability in genetic programming with polyandry. South Afr. Comput. J. 51: 22-43 (2013) - [c27]Nelishia Pillay, P. Govender:
Constrained Minimum-Variance PID Control using Hybrid Nelder-Mead Simplex and Swarm Intelligence. ICAART (2) 2013: 330-337 - [c26]Rushil Raghavjee, Nelishia Pillay:
A Study of Genetic Algorithms to Solve the School Timetabling Problem. MICAI (2) 2013: 64-80 - [c25]Kevin Igwe, Nelishia Pillay, Christopher Rae:
Solving the 8-puzzle problem using genetic programming. SAICSIT 2013: 64-67 - [c24]Nelishia Pillay:
A comparative study of hyper-heuristics for solving the school timetabling problem. SAICSIT 2013: 278-285 - 2012
- [j11]Nelishia Pillay:
Evolving hyper-heuristics for the uncapacitated examination timetabling problem. J. Oper. Res. Soc. 63(1): 47-58 (2012) - [j10]Nelishia Pillay:
A study of evolutionary algorithm selection hyper-heuristics for the one-dimensional bin-packing problem. South Afr. Comput. J. 48: 31-40 (2012) - [j9]Nelishia Pillay:
Finding solutions to sudoku puzzles using human intuitive heuristics. South Afr. Comput. J. 49: 25-34 (2012) - [c23]Rushil Raghavjee, Nelishia Pillay:
A comparison of genetic algorithms and genetic programming in solving the school timetabling problem. NaBIC 2012: 98-103 - [c22]Anisa W. Ragalo, Nelishia Pillay:
A building block conservation and extension mechanism for improved performance in Polynomial Symbolic Regression tree-based Genetic Programming. NaBIC 2012: 123-129 - [c21]Christopher Rae, Nelishia Pillay:
A preliminary study into the use of an evolutionary algorithm hyper-heuristic to solve the nurse rostering problem. NaBIC 2012: 156-161 - 2011
- [c20]Rushil Raghavjee, Nelishia Pillay:
The effect of construction heuristics on the performance of a genetic algorithm for the school timetabling problem. SAICSIT 2011: 187-194 - 2010
- [j8]Nelishia Pillay, Wolfgang Banzhaf:
An informed genetic algorithm for the examination timetabling problem. Appl. Soft Comput. 10(2): 457-467 (2010) - [c19]Rushil Raghavjee, Nelishia Pillay:
Using genetic algorithms to solve the South African school timetabling problem. NaBIC 2010: 286-292 - [c18]Rosanne Els, Nelishia Pillay:
An evolutionary algorithm hyper-heuristic for producing feasible timetables for the curriculum based university course timetabling problem. NaBIC 2010: 460-466 - [c17]Nelishia Pillay:
An empirical study into the structure of heuristic combinations in an evolutionary algorithm hyper-heuristic for the examination timetabling problem. SAICSIT 2010: 251-257 - [c16]Nelishia Pillay:
A study into the use of hyper-heuristics to solve the school timetabling problem. SAICSIT 2010: 258-264 - [c15]Rushil Raghavjee, Nelishia Pillay:
An informed genetic algorithm for the high school timetabling problem. SAICSIT 2010: 408-412
2000 – 2009
- 2009
- [j7]Nelishia Pillay, Wolfgang Banzhaf:
A study of heuristic combinations for hyper-heuristic systems for the uncapacitated examination timetabling problem. Eur. J. Oper. Res. 197(2): 482-491 (2009) - [j6]Nelishia Pillay:
Learning difficulties experienced by students in a course on formal languages and automata theory. ACM SIGCSE Bull. 41(4): 48-52 (2009) - [c14]Rushil Raghavjee, Nelishia Pillay:
Evolving Solutions to the School Timetabling Problem. NaBIC 2009: 1524-1527 - [c13]Nelishia Pillay:
The revised developmental approach to the uncapacitated examination timetabling problem. SAICSIT 2009: 187-192 - 2008
- [j5]Nelishia Pillay:
Teaching the theory of formal languages and automata in the Computer Science undergraduate curriculum. South Afr. Comput. J. 42: 87-94 (2008) - [c12]Amashini Naidoo, Nelishia Pillay:
Using Genetic Programming for Turing Machine Induction. EuroGP 2008: 350-361 - [c11]Nelishia Pillay, Wolfgang Banzhaf:
A Developmental Approach to the Uncapacitated Examination Timetabling Problem. PPSN 2008: 276-285 - [c10]Nelishia Pillay:
An analysis of representations for hyper-heuristics for the uncapacitated examination timetabling problem in a genetic programming system. SAICSIT 2008: 188-192 - [c9]Rushil Raghavjee, Nelishia Pillay:
An application of genetic algorithms to the school timetabling problem. SAICSIT 2008: 193-199 - 2007
- [j4]Wolfgang Banzhaf, Nelishia Pillay:
Why complex systems engineering needs biological development. Complex. 13(2): 12-21 (2007) - [c8]Nelishia Pillay, Wolfgang Banzhaf:
A Genetic Programming Approach to the Generation of Hyper-Heuristics for the Uncapacitated Examination Timetabling Problem. EPIA Workshops 2007: 223-234 - [c7]Amashini Naidoo, Nelishia Pillay:
The Induction of Finite Transducers Using Genetic Programming. EuroGP 2007: 371-380 - [c6]Amashini Naidoo, Nelishia Pillay:
Evolving pushdown automata. SAICSIT 2007: 83-90 - [c5]Nelishia Pillay, Caryl K. A. Chalmers:
A hybrid approach to automatic programming for the object-oriented programming paradigm. SAICSIT 2007: 116-124 - 2005
- [j3]Nelishia Pillay, Vikash R. Jugoo:
An investigation into student characteristics affecting novice programming performance. ACM SIGCSE Bull. 37(4): 107-110 (2005) - [c4]Nelishia Pillay:
An investigation into using genetic programming as a means of inducing solutions to novice procedural programming problems. GECCO 2005: 1781-1782 - 2004
- [j2]Nelishia Pillay:
A first course in genetic programming. ACM SIGCSE Bull. 36(4): 93-96 (2004) - [c3]Tanja Reinhardt, Nelishia Pillay:
Analysis of Spreadsheet Errors Made by Computer Literacy Students. ICALT 2004 - [c2]Nelishia Pillay:
A first course in genetic programming. ITiCSE-WGR 2004: 93-96 - 2003
- [j1]Nelishia Pillay:
Developing intelligent programming tutors for novice programmers. ACM SIGCSE Bull. 35(2): 78-82 (2003) - 2002
- [c1]Nelishia Pillay:
Using genetic programming for the induction of novice procedural programming solution algorithms. SAC 2002: 578-583
Coauthor Index
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