Genetic Programming Bibliography entries for Fangfang Zhang

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GP coauthors/coeditors: Zhixing Huang, Yi Mei, Mengjie Zhang, Wolfgang Banzhaf, Jordan MacLachlan, Jessica Signal, Gaofeng Shi, Meng Xu, Shiqiang Zhu, Beibei Zhang, Tian Xiang, Su Nguyen, Kay Chen Tan, Luyao Zhu, Xiaodong Zhu, Ke Chen2,

Genetic Programming Articles by Fangfang Zhang

  1. Zhixing Huang and Yi Mei and Fangfang Zhang and Mengjie Zhang and Wolfgang Banzhaf. Bridging directed acyclic graphs to linear representations in linear genetic programming: a case study of dynamic scheduling. Genetic Programming and Evolvable Machines, 25:Article no 5, 2024. Online first. details

  2. Fangfang Zhang and Yi Mei and Su Nguyen and Mengjie Zhang. Multitask Multiobjective Genetic Programming for Automated Scheduling Heuristic Learning in Dynamic Flexible Job-Shop Scheduling. IEEE Transactions on Cybernetics, 53(7):4473-4486, 2023. details

  3. Meng Xu and Yi Mei and Shiqiang Zhu and Beibei Zhang and Tian Xiang and Fangfang Zhang and Mengjie Zhang. Genetic Programming for Dynamic Workflow Scheduling in Fog Computing. IEEE Transactions on Services Computing, 16(4):2657-2671, 2023. details

  4. Fangfang Zhang and Yi Mei and Su Nguyen and Kay Chen Tan and Mengjie Zhang. Instance Rotation Based Surrogate in Genetic Programming with Brood Recombination for Dynamic Job Shop Scheduling. IEEE Transactions on Evolutionary Computation, 27(5):1192-1206, 2023. details

  5. Fangfang Zhang and Yi Mei and Su Nguyen and Kay Chen Tan and Mengjie Zhang. Task Relatedness Based Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling. IEEE Transactions on Evolutionary Computation, 27(6):1705-1719, 2023. details

  6. Fangfang Zhang and Yi Mei and Su Nguyen and Kay Chen Tan and Mengjie Zhang. Multitask Genetic Programming-Based Generative Hyperheuristics: A Case Study in Dynamic Scheduling. IEEE Transactions on Cybernetics, 52(10):10515-10528, 2022. details

  7. Fangfang Zhang and Yi Mei and Su Nguyen and Mengjie Zhang. Collaborative Multifidelity-Based Surrogate Models for Genetic Programming in Dynamic Flexible Job Shop Scheduling. IEEE Transactions on Cybernetics, 52(8):8142-8156, 2022. details

  8. Fangfang Zhang and Yi Mei and Su Nguyen and Mengjie Zhang and Kay Chen Tan. Surrogate-Assisted Evolutionary Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling. IEEE Transactions on Evolutionary Computation, 25(4):651-665, 2021. details

  9. Fangfang Zhang and Yi Mei and Su Nguyen and Mengjie Zhang. Correlation Coefficient based Recombinative Guidance for Genetic Programming Hyper-heuristics in Dynamic Flexible Job Shop Scheduling. IEEE Transactions on Evolutionary Computation, 25(3):552-566, 2021. details

  10. Fangfang Zhang and Yi Mei and Su Nguyen and Mengjie Zhang. Evolving Scheduling Heuristics via Genetic Programming With Feature Selection in Dynamic Flexible Job-Shop Scheduling. IEEE Transactions on Cybernetics, 51(4):1797-1811, 2021. details

  11. Fangfang Zhang and Yi Mei and Su Nguyen and Mengjie Zhang. Survey on Genetic Programming and Machine Learning Techniques for Heuristic Design in Job Shop Scheduling. IEEE Transactions on Evolutionary Computation. details

  12. Meng Xu and Yi Mei and Fangfang Zhang and Mengjie Zhang. Genetic Programming for Dynamic Flexible Job Shop Scheduling: Evolution With Single Individuals and Ensembles. IEEE Transactions on Evolutionary Computation. Accepted for future publication. details

  13. Meng Xu and Yi Mei and Fangfang Zhang and Mengjie Zhang. Genetic Programming with Lexicase Selection for Large-scale Dynamic Flexible Job Shop Scheduling. IEEE Transactions on Evolutionary Computation. Accepted for future publication. details

  14. Zhixing Huang and Yi Mei and Fangfang Zhang and Mengjie Zhang. Toward Evolving Dispatching Rules With Flow Control Operations By Grammar-Guided Linear Genetic Programming. IEEE Transactions on Evolutionary Computation. Accepted for future publication. details

  15. Zhixing Huang and Yi Mei and Fangfang Zhang and Mengjie Zhang. Multitask Linear Genetic Programming with Shared Individuals and its Application to Dynamic Job Shop Scheduling. IEEE Transactions on Evolutionary Computation. Accepted for future publication. details

Genetic Programming Books by Fangfang Zhang

Genetic Programming PhD doctoral thesis Fangfang Zhang

Genetic Programming conference papers by Fangfang Zhang

  1. Meng Xu and Yi Mei and Fangfang Zhang and Mengjie Zhang. A Semantic Genetic Programming Approach to Evolving Heuristics for Multi-objective Dynamic Scheduling. In Tongliang Liu and Geoff Webb and Lin Yue and Dadong Wang editors, 36th Australasian Joint Conference on Artificial Intelligence, Part II, volume 14472, pages 403-415, Brisbane, Australia, 2023. Springer Nature. details

  2. Luyao Zhu and Fangfang Zhang and Xiaodong Zhu and Ke Chen2 and Mengjie Zhang. Sample-Aware Surrogate-Assisted Genetic Programming for Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling. In Sara Silva and Luis Paquete and Leonardo Vanneschi and Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and Arnaud Liefooghe and Bing Xue and Ying Bi and Nelishia Pillay and Irene Moser and Arthur Guijt and Jessica Catarino and Pablo Garcia-Sanchez and Leonardo Trujillo and Carla Silva and Nadarajen Veerapen editors, Proceedings of the 2023 Genetic and Evolutionary Computation Conference, pages 384-392, Lisbon, Portugal, 2023. Association for Computing Machinery. details

  3. Fangfang Zhang and Yi Mei and Mengjie Zhang. An Investigation of Terminal Settings on Multitask Multi-Objective Dynamic Flexible Job Shop Scheduling with Genetic Programming. In Sara Silva and Luis Paquete and Leonardo Vanneschi and Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and Arnaud Liefooghe and Bing Xue and Ying Bi and Nelishia Pillay and Irene Moser and Arthur Guijt and Jessica Catarino and Pablo Garcia-Sanchez and Leonardo Trujillo and Carla Silva and Nadarajen Veerapen editors, Proceedings of the 2023 Genetic and Evolutionary Computation Conference, pages 259-262, Lisbon, Portugal, 2023. Association for Computing Machinery. details

  4. Fangfang Zhang and Mengjie Zhang and Yi Mei and Su Nguyen. Genetic Programming and Machine Learning for Scheduling. In Gui DeSouza and Gary Yen editors, 2023 IEEE Congress on Evolutionary Computation (CEC), Chicago, USA, 2023. details

  5. Meng Xu and Yi Mei and Fangfang Zhang and Mengjie Zhang. Multi-Objective Genetic Programming Based on Decomposition on Evolving Scheduling Heuristics for Dynamic Scheduling. In Sara Silva and Luis Paquete and Leonardo Vanneschi and Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and Arnaud Liefooghe and Bing Xue and Ying Bi and Nelishia Pillay and Irene Moser and Arthur Guijt and Jessica Catarino and Pablo Garcia-Sanchez and Leonardo Trujillo and Carla Silva and Nadarajen Veerapen editors, Proceedings of the Companion Conference on Genetic and Evolutionary Computation, pages 427-430, Lisbon, Portugal, 2023. Association for Computing Machinery. details

  6. Gaofeng Shi and Fangfang Zhang and Yi Mei. Interpretability-Aware Multi-Objective Genetic Programming for Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling. In Gui DeSouza and Gary Yen editors, 2023 IEEE Congress on Evolutionary Computation (CEC), Chicago, USA, 2023. details

  7. Jordan MacLachlan and Yi Mei and Fangfang Zhang and Mengjie Zhang and Jessica Signal. Learning Emergency Medical Dispatch Policies via Genetic Programming. In Sara Silva and Luis Paquete and Leonardo Vanneschi and Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and Arnaud Liefooghe and Bing Xue and Ying Bi and Nelishia Pillay and Irene Moser and Arthur Guijt and Jessica Catarino and Pablo Garcia-Sanchez and Leonardo Trujillo and Carla Silva and Nadarajen Veerapen editors, Proceedings of the 2023 Genetic and Evolutionary Computation Conference, pages 1409-1417, Lisbon, Portugal, 2023. Association for Computing Machinery. Silver 2023 HUMIES. details

  8. Zhixing Huang and Yi Mei and Fangfang Zhang and Mengjie Zhang. Grammar-Guided Linear Genetic Programming for Dynamic Job Shop Scheduling. In Sara Silva and Luis Paquete and Leonardo Vanneschi and Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and Arnaud Liefooghe and Bing Xue and Ying Bi and Nelishia Pillay and Irene Moser and Arthur Guijt and Jessica Catarino and Pablo Garcia-Sanchez and Leonardo Trujillo and Carla Silva and Nadarajen Veerapen editors, Proceedings of the 2023 Genetic and Evolutionary Computation Conference, pages 1137-1145, Lisbon, Portugal, 2023. Association for Computing Machinery. details

  9. Meng Xu and Yi Mei and Fangfang Zhang and Mengjie Zhang. Genetic Programming with Diverse Partner Selection for Dynamic Flexible Job Shop Scheduling. In Heike Trautmann and Carola Doerr and Alberto Moraglio and Thomas Bartz-Beielstein and Bogdan Filipic and Marcus Gallagher and Yew-Soon Ong and Abhishek Gupta and Anna V Kononova and Hao Wang and Michael Emmerich and Peter A. N. Bosman and Daniela Zaharie and Fabio Caraffini and Johann Dreo and Anne Auger and Konstantin Dietric and Paul Dufosse and Tobias Glasmachers and Nikolaus Hansen and Olaf Mersmann and Petr Posik and Tea Tusar and Dimo Brockhoff and Tome Eftimov and Pascal Kerschke and Boris Naujoks and Mike Preuss and Vanessa Volz and Bilel Derbel and Ke Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Mark Coletti and Catherine (Katie) Schuman and Eric ``Siggy'' Scott and Robert Patton and Paul Wiegand and Jeffrey K. Bassett and Chathika Gunaratne and Tinkle Chugh and Richard Allmendinger and Jussi Hakanen and Daniel Tauritz and John Woodward and Manuel Lopez-Ibanez and John McCall and Jaume Bacardit and Alexander Brownlee and Stefano Cagnoni and Giovanni Iacca and David Walker and Jamal Toutouh and UnaMay O'Reilly and Penousal Machado and Joao Correia and Sergio Nesmachnow and Josu Ceberio and Rafael Villanueva and Ignacio Hidalgo and Francisco Fernandez de Vega and Giuseppe Paolo and Alex Coninx and Antoine Cully and Adam Gaier and Stefan Wagner and Michael Affenzeller and Bobby R. Bruce and Vesna Nowack and Aymeric Blot and Emily Winter and William B. Langdon and Justyna Petke and Silvino Fernandez Alzueta and Pablo Valledor Pellicer and Thomas Stuetzle and David Paetzel and Alexander Wagner and Michael Heider and Nadarajen Veerapen and Katherine Malan and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa and Mohammad Nabi Omidvar and Yuan Sun and Ernesto Tarantino and De Falco Ivanoe and Antonio Della Cioppa and Scafuri Umberto and John Rieffel and Jean-Baptiste Mouret and Stephane Doncieux and Stefanos Nikolaidis and Julian Togelius and Matthew C. Fontaine and Serban Georgescu and Francisco Chicano and Darrell Whitley and Oleksandr Kyriienko and Denny Dahl and Ofer Shir and Lee Spector and Alma Rahat and Richard Everson and Jonathan Fieldsend and Handing Wang and Yaochu Jin and Erik Hemberg and Marwa A. Elsayed and Michael Kommenda and William La Cava and Gabriel Kronberger and Steven Gustafson editors, Proceedings of the 2022 Genetic and Evolutionary Computation Conference Companion, pages 615-618, Boston, USA, 2022. Association for Computing Machinery. details

  10. Zhixing Huang and Yi Mei and Fangfang Zhang and Mengjie Zhang. Graph-based Linear Genetic Programming: A Case Study of Dynamic Scheduling. In Alma Rahat and Jonathan Fieldsend and Markus Wagner and Sara Tari and Nelishia Pillay and Irene Moser and Aldeida Aleti and Ales Zamuda and Ahmed Kheiri and Erik Hemberg and Christopher Cleghorn and Chao-li Sun and Georgios Yannakakis and Nicolas Bredeche and Gabriela Ochoa and Bilel Derbel and Gisele L. Pappa and Sebastian Risi and Laetitia Jourdan and Hiroyuki Sato and Petr Posik and Ofer Shir and Renato Tinos and John Woodward and Malcolm Heywood and Elizabeth Wanner and Leonardo Trujillo and Domagoj Jakobovic and Risto Miikkulainen and Bing Xue and Aneta Neumann and Richard Allmendinger and Inmaculada Medina-Bulo and Slim Bechikh and Andrew M. Sutton and Pietro Simone Oliveto editors, Proceedings of the 2022 Genetic and Evolutionary Computation Conference, pages 955-963, Boston, USA, 2022. Association for Computing Machinery. details

  11. Fangfang Zhang and Yi Mei and Su Nguyen and Mengjie Zhang. Phenotype Based Surrogate-Assisted Multi-objective Genetic Programming with Brood Recombination for Dynamic Flexible Job Shop Scheduling. In 2022 IEEE Symposium Series on Computational Intelligence (SSCI), pages 1218-1225, 2022. details

  12. Fangfang Zhang and Yi Mei and Su Nguyen and Mengjie Zhang. Learning Strategies on Scheduling Heuristics of Genetic Programming in Dynamic Flexible Job Shop Scheduling. In Carlos A. Coello Coello and Sanaz Mostaghim editors, 2022 IEEE Congress on Evolutionary Computation (CEC), Padua, Italy, 2022. details

  13. Meng Xu and Fangfang Zhang and Yi Mei and Mengjie Zhang. Genetic Programming with Multi-case Fitness for Dynamic Flexible Job Shop Scheduling. In 2022 IEEE Congress on Evolutionary Computation (CEC), 2022. details

  14. Meng Xu and Yi Mei and Fangfang Zhang and Mengjie Zhang. Genetic Programming with Cluster Selection for Dynamic Flexible Job Shop Scheduling. In Carlos A. Coello Coello and Sanaz Mostaghim editors, 2022 IEEE Congress on Evolutionary Computation (CEC), Padua, Italy, 2022. details

  15. Gaofeng Shi and Fangfang Zhang and Yi Mei. A Novel Fitness Function for Genetic Programming in Dynamic Flexible Job Shop Scheduling. In Carlos A. Coello Coello and Sanaz Mostaghim editors, 2022 IEEE Congress on Evolutionary Computation (CEC), Padua, Italy, 2022. details

  16. Jordan MacLachlan and Yi Mei and Fangfang Zhang and Mengjie Zhang. Genetic Programming for Vehicle Subset Selection in Ambulance Dispatching. In Carlos A. Coello Coello and Sanaz Mostaghim editors, 2022 IEEE Congress on Evolutionary Computation (CEC), Padua, Italy, 2022. details

  17. Zhixing Huang and Yi Mei and Fangfang Zhang and Mengjie Zhang. A Further Investigation to Improve Linear Genetic Programming in Dynamic Job Shop Scheduling. In 2022 IEEE Symposium Series on Computational Intelligence (SSCI), pages 496-503, 2022. details

  18. Zhixing Huang and Fangfang Zhang and Yi Mei and Mengjie Zhang. An Investigation of Multitask Linear Genetic Programming for Dynamic Job Shop Scheduling. In Eric Medvet and Gisele Pappa and Bing Xue editors, EuroGP 2022: Proceedings of the 25th European Conference on Genetic Programming, volume 13223, pages 162-178, Madrid, Spain, 2022. Springer Verlag. Best paper. details

  19. Fangfang Zhang and Yi Mei and Su Nguyen and Mengjie Zhang. Importance-Aware Genetic Programming for Automated Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling. In Guenter Rudolph and Anna V. Kononova and Hernan E. Aguirre and Pascal Kerschke and Gabriela Ochoa and Tea Tusar editors, Parallel Problem Solving from Nature - PPSN XVII - 17th International Conference, PPSN 2022, Proceedings, Part II, volume 13399, pages 48-62, Dortmund, Germany, 2022. Springer. details

  20. Fangfang Zhang and Su Nguyen and Yi Mei and Mengjie Zhang. Adaptive Multitask Genetic Programming for Dynamic Job Shop Scheduling. In Genetic Programming for Production Scheduling, 2021. Springer. details

  21. Meng Xu and Fangfang Zhang and Yi Mei and Mengjie Zhang. Genetic Programming with Archive for Dynamic Flexible Job Shop Scheduling. In Yew-Soon Ong editor, 2021 IEEE Congress on Evolutionary Computation (CEC), pages 2117-2124, Krakow, Poland, 2021. details

  22. Fangfang Zhang and Yi Mei and Su Nguyen and Mengjie Zhang. Genetic Programming with Adaptive Search Based on the Frequency of Features for Dynamic Flexible Job Shop Scheduling. In L. Paquete and C. Zarges editors, European Conference on Evolutionary Computation in Combinatorial Optimization (EvoCOP 2020), volume 12102, pages 214-230, Seville, Spain, 2020. Springer Verlag. details

  23. Fangfang Zhang and Yi Mei and Su Nguyen and Mengjie Zhang. A Preliminary Approach to Evolutionary Multitasking for Dynamic Flexible Job Shop Scheduling via Genetic Programming. In Richard Allmendinger and Hugo Terashima Marin and Efren Mezura Montes and Thomas Bartz-Beielstein and Bogdan Filipic and Ke Tang and David Howard and Emma Hart and Gusz Eiben and Tome Eftimov and William La Cava and Boris Naujoks and Pietro Oliveto and Vanessa Volz and Thomas Weise and Bilel Derbel and Ke Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Rui Wang and Ran Cheng and Guohua Wu and Miqing Li and Hisao Ishibuchi and Jonathan Fieldsend and Ozgur Akman and Khulood Alyahya and Juergen Branke and John R. Woodward and Daniel R. Tauritz and Marco Baioletti and Josu Ceberio Uribe and John McCall and Alfredo Milani and Stefan Wagner and Michael Affenzeller and Bradley Alexander and Alexander (Sandy) Brownlee and Saemundur O. Haraldsson and Markus Wagner and Nayat Sanchez-Pi and Luis Marti and Silvino Fernandez Alzueta and Pablo Valledor Pellicer and Thomas Stuetzle and Matthew Johns and Nick Ross and Ed Keedwell and Herman Mahmoud and David Walker and Anthony Stein and Masaya Nakata and David Paetzel and Neil Vaughan and Stephen Smith and Stefano Cagnoni and Robert M. Patton and Ivanoe De Falco and Antonio Della Cioppa and Umberto Scafuri and Ernesto Tarantino and Akira Oyama and Koji Shimoyama and Hemant Kumar Singh and Kazuhisa Chiba and Pramudita Satria Palar and Alma Rahat and Richard Everson and Handing Wang and Yaochu Jin and Erik Hemberg and Riyad Alshammari and Tokunbo Makanju and Fuijimino-shi and Ivan Zelinka and Swagatam Das and Ponnuthurai Nagaratnam and Roman Senkerik editors, Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, pages 107-108, internet, 2020. Association for Computing Machinery. details

  24. Fangfang Zhang and Yi Mei and Su Nguyen and Mengjie Zhang. Guided Subtree Selection for Genetic Operators in Genetic Programming for Dynamic Flexible Job Shop Scheduling. In Ting Hu and Nuno Lourenco and Eric Medvet editors, EuroGP 2020: Proceedings of the 23rd European Conference on Genetic Programming, volume 12101, pages 262-278, Seville, Spain, 2020. Springer Verlag. details

  25. Fangfang Zhang and Yi Mei and Mengjie Zhang. A New Representation in Genetic Programming for Evolving Dispatching Rules for Dynamic Flexible Job Shop Scheduling. In A. Liefooghe and L. Paquete editors, The 19th European Conference on Evolutionary Computation in Combinatorial Optimisation, EvoCOP 2019, volume 11452, pages 33-49, 2019. Springer. details

  26. Fangfang Zhang and Yi Mei and Mengjie Zhang. A Two-stage Genetic Programming Hyper-heuristic Approach with Feature Selection for Dynamic Flexible Job Shop Scheduling. In Manuel Lopez-Ibanez and Thomas Stuetzle and Anne Auger and Petr Posik and Leslie Peprez Caceres and Andrew M. Sutton and Nadarajen Veerapen and Christine Solnon and Andries Engelbrecht and Stephane Doncieux and Sebastian Risi and Penousal Machado and Vanessa Volz and Christian Blum and Francisco Chicano and Bing Xue and Jean-Baptiste Mouret and Arnaud Liefooghe and Jonathan Fieldsend and Jose Antonio Lozano and Dirk Arnold and Gabriela Ochoa and Tian-Li Yu and Holger Hoos and Yaochu Jin and Ting Hu and Miguel Nicolau and Robin Purshouse and Thomas Baeck and Justyna Petke and Giuliano Antoniol and Johannes Lengler and Per Kristian Lehre editors, GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference, pages 347-355, Prague, Czech Republic, 2019. ACM. details

  27. Fangfang Zhang and Yi Mei and Mengjie Zhang. Evolving Dispatching Rules for Multi-objective Dynamic Flexible Job Shop Scheduling via Genetic Programming Hyper-heuristics. In Carlos A. Coello Coello editor, 2019 IEEE Congress on Evolutionary Computation, CEC 2019, pages 1366-1373, Wellington, New Zealand, 2019. IEEE Press. details

  28. Fangfang Zhang and Yi Mei and Mengjie Zhang. Can Stochastic Dispatching Rules Evolved by Genetic Programming Hyper-heuristics Help in Dynamic Flexible Job Shop Scheduling?. In Carlos A. Coello Coello editor, 2019 IEEE Congress on Evolutionary Computation, CEC 2019, pages 41-48, Wellington, New Zealand, 2019. IEEE Press. details

  29. Fangfang Zhang and Yi Mei and Mengjie Zhang. Surrogate-Assisted Genetic Programming for Dynamic Flexible Job Shop Scheduling. In Tanja Mitrovic and Bing Xue and Xiaodong Li editors, Australasian Joint Conference on Artificial Intelligence, volume 11320, pages 766-772, Wellington, New Zealand, 2018. Springer. details

  30. Fangfang Zhang and Yi Mei and Mengjie Zhang. Genetic Programming with Multi-tree Representation for Dynamic Flexible Job Shop Scheduling. In Tanja Mitrovic and Bing Xue and Xiaodong Li editors, Australasian Joint Conference on Artificial Intelligence, volume 11320, pages 472-484, Wellington, New Zealand, 2018. Springer. details