Genetic Programming Bibliography entries for Zhixing Huang

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GP coauthors/coeditors: Jinghui Zhong, Weili Liu, Zhou Wu, Chengyu Lu, Liang Feng, Yi Mei, Wentong Cai, Mengjie Zhang, Fangfang Zhang, Wolfgang Banzhaf, Ying Li, Ruihua Zeng, Yongliang Chen, Yusen Lin, Wan Du,

Genetic Programming Articles by Zhixing Huang

  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. Jinghui Zhong and Zhixing Huang and Liang Feng and Wan Du and Ying Li. A hyper-heuristic framework for lifetime maximization in wireless sensor networks with a mobile sink. IEEE/CAA Journal of Automatica Sinica, 7(1):223-236, 2020. details

  3. Zhixing Huang and Jinghui Zhong and Liang Feng and Yi Mei and Wentong Cai. A fast parallel genetic programming framework with adaptively weighted primitives for symbolic regression. Soft Comput., 24(10):7523-7539, 2020. details

  4. 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

  5. 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

  6. Zhixing Huang and Yi Mei and Jinghui Zhong. Semantic Linear Genetic Programming for Symbolic Regression. IEEE Transactions on Cybernetics. Early Access. details

Genetic Programming conference papers by Zhixing Huang

  1. 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

  2. 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

  3. 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

  4. 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

  5. Zhixing Huang and Yi Mei and Mengjie Zhang. Investigation of Linear Genetic Programming for Dynamic Job Shop Scheduling. In IEEE Symposium Series on Computational Intelligence, SSCI 2021, Orlando, FL, USA, December 5-7, 2021, 2021. IEEE. details

  6. Ruihua Zeng and Zhixing Huang and Yongliang Chen and Jinghui Zhong and Liang Feng. Comparison of Different Computing Platforms for Implementing Parallel Genetic Programming. In Yaochu Jin editor, 2020 IEEE Congress on Evolutionary Computation, CEC 2020, page paper id24270, internet, 2020. IEEE Press. details

  7. Zhixing Huang and Chengyu Lu and Jinghui Zhong. A Multi-Objective Hyper-Heuristic for Unmanned Aerial Vehicle Data Collection in Wireless Sensor Networks. In 2019 IEEE Symposium Series on Computational Intelligence (SSCI), pages 1614-1621, 2019. details

  8. Jinghui Zhong and Yusen Lin and Chengyu Lu and Zhixing Huang. A Deep Learning Assisted Gene Expression Programming Framework for Symbolic Regression Problems. In Long Cheng and Andrew Chi-Sing Leung and Seiichi Ozawa editors, Neural Information Processing - 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13-16, 2018, Proceedings, Part VII, volume 11307, pages 530-541, 2018. Springer. details

  9. Zhixing Huang and Jinghui Zhong and Weili Liu and Zhou Wu. Multi-population genetic programming with adaptively weighted building blocks for symbolic regression. In Carlos Cotta and Tapabrata Ray and Hisao Ishibuchi and Shigeru Obayashi and Bogdan Filipic and Thomas Bartz-Beielstein and Grant Dick and Masaharu Munetomo and Silvino Fernandez Alzueta and Thomas Stuetzle and Pablo Valledor Pellicer and Manuel Lopez-Ibanez and Daniel R. Tauritz and Pietro S. Oliveto and Thomas Weise and Borys Wrobel and Ales Zamuda and Anne Auger and Julien Bect and Dimo Brockhoff and Nikolaus Hansen and Rodolphe Le Riche and Victor Picheny and Bilel Derbel and Ke Li and Hui Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Stephane Doncieux and Richard Duro and Joshua Auerbach and Harold de Vladar and Antonio J. Fernandez-Leiva and JJ Merelo and Pedro A. Castillo-Valdivieso and David Camacho-Fernandez and Francisco Chavez de la O and Ozgur Akman and Khulood Alyahya and Juergen Branke and Kevin Doherty and Jonathan Fieldsend and Giuseppe Carlo Marano and Nikos D. Lagaros and Koichi Nakayama and Chika Oshima and Stefan Wagner and Michael Affenzeller and Boris Naujoks and Vanessa Volz and Tea Tusar and Pascal Kerschke and Riyad Alshammari and Tokunbo Makanju and Brad Alexander and Saemundur O. Haraldsson and Markus Wagner and John R. Woodward and Shin Yoo and John McCall and Nayat Sanchez-Pi and Luis Marti and Danilo Vasconcellos and Masaya Nakata and Anthony Stein and Nadarajen Veerapen and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa and Stephen L. Smith and Stefano Cagnoni and Robert M. Patton and William La Cava and Randal Olson and Patryk Orzechowski and Ryan Urbanowicz and Ivanoe De Falco and Antonio Della Cioppa and Ernesto Tarantino and Umberto Scafuri and P. G. M. Baltus and Giovanni Iacca and Ahmed Hallawa and Anil Yaman and Alma Rahat and Handing Wang and Yaochu Jin and David Walker and Richard Everson and Akira Oyama and Koji Shimoyama and Hemant Kumar and Kazuhisa Chiba and Pramudita Satria Palar editors, GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 266-267, Kyoto, Japan, 2018. ACM. details

  10. Ying Li and Zhixing Huang and Jinghui Zhong and Liang Feng. Genetic Programming for Lifetime Maximization in Wireless Sensor Networks with a Mobile Sink. In Yuhui Shi and Kay Chen Tan and Mengjie Zhang and Ke Tang and Xiaodong Li and Qingfu Zhang and Ying Tan and Martin Middendorf and Yaochu Jin editors, Proceedings of the 11th International Conference on Simulated Evolution and Learning, SEAL-2017, volume 10593, pages 774-785, Shenzhen, China, 2017. Springer. details