Genetic Programming Bibliography entries for Tapabrata Ray

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GP coauthors/coeditors: Shelvin Chand, Quang Nhat Huynh, Hemant Singh, Markus Wagner, Hemant Kumar Singh, Akira Oyama, Angus Kenny, Steffen Limmer, Tobias Rodemann, Markus Olhofer, Bing Wang,

Genetic Programming Articles by Tapabrata Ray

  1. Shelvin Chand and Hemant Singh and Tapabrata Ray. Evolving rollout-justification based heuristics for resource constrained project scheduling problems. Swarm and Evolutionary Computation, 50:100556, 2019. details

  2. Shelvin Chand and Hemant Singh and Tapabrata Ray. Evolving heuristics for the resource constrained project scheduling problem with dynamic resource disruptions. Swarm and Evolutionary Computation, 44:897-912, 2019. details

  3. Quang Nhat Huynh and Shelvin Chand and Hemant Kumar Singh and Tapabrata Ray. Genetic Programming with Mixed Integer Linear Programming Based Library Search. IEEE Transactions on Evolutionary Computation, 22(5):733-747, 2018. details

  4. Shelvin Chand and Quang Huynh and Hemant Singh and Tapabrata Ray and Markus Wagner. On the use of genetic programming to evolve priority rules for resource constrained project scheduling problems. Information Sciences, 432:146-163, 2018. details

Genetic Programming conference papers by Tapabrata Ray

  1. Angus Kenny and Tapabrata Ray and Steffen Limmer and Hemant Kumar Singh and Tobias Rodemann and Markus Olhofer. Hybridizing TPOT with Bayesian Optimization. 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 502-510, Lisbon, Portugal, 2023. Association for Computing Machinery. details

  2. Quang Huynh and Hemant Singh and Tapabrata Ray and Akira Oyama. Improved Genetic Programming for Symbolic Regression: Case Studies on Practical Applications. In 2022 IEEE Symposium Series on Computational Intelligence (SSCI), pages 1135-1142, 2022. details

  3. Quang Nhat Huynh and Hemant Kumar Singh and Tapabrata Ray. Improving Symbolic Regression through a semantics-driven framework. In 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 2016. details

  4. Quang Nhat Huynh and Hemant Kumar Singh and Tapabrata Ray. A Semantics based Symbolic Regression Framework for Mining Explicit and Implicit Equations from Data. In Tobias Friedrich and Frank Neumann and Andrew M. Sutton and Martin Middendorf and Xiaodong Li and Emma Hart and Mengjie Zhang and Youhei Akimoto and Peter A. N. Bosman and Terry Soule and Risto Miikkulainen and Daniele Loiacono and Julian Togelius and Manuel Lopez-Ibanez and Holger Hoos and Julia Handl and Faustino Gomez and Carlos M. Fonseca and Heike Trautmann and Alberto Moraglio and William F. Punch and Krzysztof Krawiec and Zdenek Vasicek and Thomas Jansen and Jim Smith and Simone Ludwig and JJ Merelo and Boris Naujoks and Enrique Alba and Gabriela Ochoa and Simon Poulding and Dirk Sudholt and Timo Koetzing editors, GECCO '16 Companion: Proceedings of the Companion Publication of the 2016 Annual Conference on Genetic and Evolutionary Computation, pages 103-104, Denver, USA, 2016. ACM. details

  5. Bing Wang and Hemant Singh and Tapabrata Ray. A Multi-objective Genetic Programming Approach to Uncover Explicit and Implicit Equations from Data. In Yadahiko Murata editor, Proceedings of 2015 IEEE Congress on Evolutionary Computation (CEC 2015), pages 1129-1136, Sendai, Japan, 2015. IEEE Press. details