Genetic Programming Bibliography entries for Aaron Chen

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GP coauthors/coeditors: Yuheng Chen, Tao Shi, Hui Ma, Kirita-Rose Escott, Josiah Jacobsen-Grocott, Yi Mei, Mengjie Zhang, Deepak Karunakaran, Atiya Masood, Harith Al-Sahaf, Su Nguyen, John Park, Chen Wang, Sven Hartmann, Victoria Huang, Yongbo Yu, Kameron Christopher, Yifan Yang, Yalian Feng,

Genetic Programming Articles by Aaron Chen

Genetic Programming conference papers by Aaron Chen

  1. Chen Wang and Hui Ma and Gang Chen2 and Victoria Huang and Yongbo Yu and Kameron Christopher. Energy-Aware Dynamic Resource Allocation in Container-Based Clouds via Cooperative Coevolution Genetic Programming. In Joao Correia and Stephen Smith and Raneem Qaddoura editors, 26th International Conference, EvoApplications 2023, volume 13989, pages 539-555, Brno, Czech Republic, 2023. Springer Verlag. details

  2. Atiya Masood and Gang Chen2 and Yi Mei and Harith Al-Sahaf and Mengjie Zhang. Genetic Programming with Adaptive Reference Points for Pareto Local Search in Many-Objective Job Shop 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 466-478, Brisbane, Australia, 2023. Springer Nature. details

  3. Kirita-Rose Escott and Hui Ma and Gang Chen2. Cooperative Coevolutionary Genetic Programming Hyper-Heuristic for Budget Constrained Dynamic Multi-workflow Scheduling in Cloud Computing. In Leslie Perez Caceres and Thomas Stuetzle editors, 23rd European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2023, volume 13987, pages 146-161, Brno, Czech Republic, 2023. Springer. details

  4. Yuheng Chen and Tao Shi and Hui Ma and Gang Chen2. Multi-objective Location-Aware Service Brokering in Multi-cloud - A GPHH Approach with Transfer Learning. In Joao Correia and Stephen Smith and Raneem Qaddoura editors, 26th International Conference, EvoApplications 2023, volume 13989, pages 573-587, Brno, Czech Republic, 2023. Springer Verlag. details

  5. Yifan Yang and Gang Chen2 and Hui Ma and Mengjie Zhang. Dual-Tree Genetic Programming for Deadline-Constrained Dynamic Workflow Scheduling in Cloud. In Service-Oriented Computing, 2022. Springer. details

  6. Yongbo Yu and Tao Shi and Hui Ma and Gang Chen2. A Genetic Programming-Based Hyper-Heuristic Approach for Multi-Objective Dynamic Workflow Scheduling in Cloud Environment. In Carlos A. Coello Coello and Sanaz Mostaghim editors, 2022 IEEE Congress on Evolutionary Computation (CEC), Padua, Italy, 2022. details

  7. Atiya Masood and Gang Chen2 and Yi Mei and Harith Al-Sahaf and Mengjie Zhang. Genetic Programming Hyper-heuristic with Gaussian Process-based Reference Point Adaption for Many-Objective Job Shop Scheduling. In Carlos A. Coello Coello and Sanaz Mostaghim editors, 2022 IEEE Congress on Evolutionary Computation (CEC), Padua, Italy, 2022. details

  8. Yuheng Chen and Tao Shi and Hui Ma and Gang Chen2. Automatically Design Heuristics for Multi-Objective Location-Aware Service Brokering in Multi-Cloud. In 2022 IEEE International Conference on Services Computing (SCC), pages 206-214, Barcelona, Spain, 2022. details

  9. Yongbo Yu and Hui Ma and Gang Chen2. Achieving Multi-Objective Scheduling of Heterogeneous Workflows in Cloud through a Genetic Programming Based Approach. In Yew-Soon Ong editor, 2021 IEEE Congress on Evolutionary Computation (CEC), pages 1880-1887, Krakow, Poland, 2021. details

  10. Yifan Yang and Gang Chen2 and Hui Ma and Mengjie Zhang and Victoria Huang. Budget and SLA Aware Dynamic Workflow Scheduling in Cloud Computing with Heterogeneous Resources. In Yew-Soon Ong editor, 2021 IEEE Congress on Evolutionary Computation (CEC), pages 2141-2148, Krakow, Poland, 2021. details

  11. Atiya Masood and Gang Chen2 and Mengjie Zhang. Feature Selection for Evolving Many-Objective Job Shop Scheduling Dispatching Rules with Genetic Programming. In Yew-Soon Ong editor, 2021 IEEE Congress on Evolutionary Computation (CEC), pages 644-651, Krakow, Poland, 2021. details

  12. Kirita-Rose Escott and Hui Ma and Gang Chen2. A Genetic Programming Hyper-Heuristic Approach to Design High-Level Heuristics for Dynamic Workflow Scheduling in Cloud. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI), pages 3141-3148, 2020. details

  13. Kirita-Rose Escott and Hui Ma and Gang Chen2. Genetic Programming Based Hyper Heuristic Approach for Dynamic Workflow Scheduling in the Cloud. In Sven Hartmann and Josef Kueng and Gabriele Kotsis and A Min Tjoa and Ismail Khalil editors, Database and Expert Systems Applications - 31st International Conference, DEXA 2020, Bratislava, Slovakia, September 14-17, 2020, Proceedings, Part II, volume 12392, pages 76-90, 2020. Springer. details

  14. Yongbo Yu and Yalian Feng and Hui Ma and Aaron Chen and Chen Wang. Achieving Flexible Scheduling of Heterogeneous Workflows in Cloud through a Genetic Programming Based Approach. In 2019 IEEE Congress on Evolutionary Computation (CEC), pages 3102-3109, 2019. details

  15. Deepak Karunakaran and Yi Mei and Gang Chen2 and Mengjie Zhang. Active Sampling for Dynamic Job Shop Scheduling using Genetic Programming. In Carlos A. Coello Coello editor, 2019 IEEE Congress on Evolutionary Computation, CEC 2019, pages 434-441, Wellington, New Zealand, 2019. IEEE Press. details

  16. Atiya Masood and Gang Chen2 and Yi Mei and Harith Al-Sahaf and Mengjie Zhang. Genetic Programming with Pareto Local Search for Many-Objective Job Shop Scheduling. In Jixue Liu and James Bailey editors, AI 2019: Advances in Artificial Intelligence - 32nd Australasian Joint Conference, Adelaide, SA, Australia, December 2-5, 2019, Proceedings, volume 11919, pages 536-548, 2019. Springer. details

  17. John Park and Yi Mei and Su Nguyen and Gang Chen2 and Mengjie Zhang. Evolutionary Multitask Optimisation for Dynamic Job Shop Scheduling Using Niched Genetic Programming. In Tanja Mitrovic and Bing Xue and Xiaodong Li editors, Australasian Joint Conference on Artificial Intelligence, volume 11320, Wellington, New Zealand, 2018. Springer. details

  18. John Park and Yi Mei and Su Nguyen and Gang Chen2 and Mengjie Zhang. Investigating a Machine Breakdown Genetic Programming Approach for Dynamic Job Shop Scheduling. In Mauro Castelli and Lukas Sekanina and Mengjie Zhang and Stefano Cagnoni and Pablo Garcia-Sanchez editors, EuroGP 2018: Proceedings of the 21st European Conference on Genetic Programming, volume 10781, pages 253-270, Parma, Italy, 2018. Springer Verlag. details

  19. Atiya Masood and Gang Chen2 and Yi Mei and Mengjie Zhang. Reference Point Adaption Method for Genetic Programming Hyper-Heuristic in Many-Objective Job Shop Scheduling. In Arnaud Liefooghe and Manuel Lopez-Ibanez editors, The 18th European Conference on Evolutionary Computation in Combinatorial Optimisation, EvoCOP 2018, volume 10782, pages 116-131, Parma, Italy, 2018. Springer. details

  20. Deepak Karunakaran and Yi Mei and Gang Chen2 and Mengjie Zhang. Sampling Heuristics for Multi-Objective Dynamic Job Shop Scheduling Using Island Based Parallel Genetic Programming. In Anne Auger and Carlos M. Fonseca and Nuno Lourenco and Penousal Machado and Luis Paquete and Darrell Whitley editors, 15th International Conference on Parallel Problem Solving from Nature, volume 11102, pages 347-359, Coimbra, Portugal, 2018. Springer. details

  21. Deepak Karunakaran and Yi Mei and Gang Chen2 and Mengjie Zhang. Dynamic Job Shop Scheduling Under Uncertainty Using Genetic Programming. In Intelligent and Evolutionary Systems, 2017. Springer. details

  22. Deepak Karunakaran and Yi Mei and Gang Chen2 and Mengjie Zhang. Evolving dispatching rules for dynamic Job shop scheduling with uncertain processing times. In Jose A. Lozano editor, 2017 IEEE Congress on Evolutionary Computation (CEC), pages 364-371, Donostia, San Sebastian, Spain, 2017. IEEE. details

  23. Josiah Jacobsen-Grocott and Yi Mei and Gang Chen2 and Mengjie Zhang. Evolving heuristics for Dynamic Vehicle Routing with Time Windows using genetic programming. In Jose A. Lozano editor, 2017 IEEE Congress on Evolutionary Computation (CEC), pages 1948-1955, Donostia, San Sebastian, Spain, 2017. IEEE. details

  24. John Park and Yi Mei and Su Nguyen and Gang Chen2 and Mengjie Zhang. Investigating the Generality of Genetic Programming Based Hyper-heuristic Approach to Dynamic Job Shop Scheduling with Machine Breakdown. In Markus Wagner and Xiaodong Li and Tim Hendtlass editors, Artificial Life and Computational Intelligence - Third Australasian Conference, ACALCI 2017, Geelong, VIC, Australia, January 31 - February 2, 2017, Proceedings, volume 10142, pages 301-313, 2017. details

  25. Atiya Masood and Yi Mei and Gang Chen2 and Mengjie Zhang. A PSO-Based Reference Point Adaption Method for Genetic Programming Hyper-Heuristic in Many-Objective Job Shop Scheduling. In Markus Wagner and Xiaodong Li and Tim Hendtlass editors, Artificial Life and Computational Intelligence - Third Australasian Conference, ACALCI 2017, Geelong, VIC, Australia, January 31 - February 2, 2017, Proceedings, volume 10142, pages 326-338, 2017. details

  26. Chen Wang and Hui Ma and Aaron Chen and Sven Hartmann. GP-Based Approach to Comprehensive Quality-Aware Automated Semantic Web Service Composition. 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 170-183, Shenzhen, China, 2017. Springer. details

  27. Deepak Karunakaran and Yi Mei and Gang Chen2 and Mengjie Zhang. Toward Evolving Dispatching Rules for Dynamic Job Shop Scheduling Under Uncertainty. In Proceedings of the Genetic and Evolutionary Computation Conference, pages 282-289, Berlin, Germany, 2017. ACM. details

  28. Deepak Karunakaran and Gang Chen2 and Mengjie Zhang. Parallel Multi-objective Job Shop Scheduling Using Genetic Programming. In Tapabrata Ray and Ruhul A. Sarker and Xiaodong Li editors, Artificial Life and Computational Intelligence - Second Australasian Conference, ACALCI 2016, Canberra, ACT, Australia, February 2-5, 2016, Proceedings, volume 9592, pages 234-245, 2016. Springer. details

  29. John Park and Yi Mei and Gang Chen2 and Mengjie Zhang. Niching Genetic Programming based Hyper-heuristic Approach to Dynamic Job Shop Scheduling: An Investigation into Distance Metrics. 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 109-110, Denver, USA, 2016. ACM. details

  30. John Park and Yi Mei and Su Nguyen and Gang Chen2 and Mengjie Zhang. Genetic Programming based Hyper-heuristics for Dynamic Job Shop Scheduling: Cooperative Coevolutionary Approaches. In Malcolm I. Heywood and James McDermott and Mauro Castelli and Ernesto Costa and Kevin Sim editors, EuroGP 2016: Proceedings of the 19th European Conference on Genetic Programming, volume 9594, pages 115-132, Porto, Portugal, 2016. Springer Verlag. details

  31. Su Nguyen and Yi Mei and Hui Ma and Aaron Chen and Mengjie Zhang. Evolutionary Scheduling and Combinatorial Optimisation: Applications, Challenges, and Future Directions. In Yew-Soon Ong editor, Proceedings of 2016 IEEE Congress on Evolutionary Computation (CEC 2016), pages 3053-3060, Vancouver, 2016. IEEE Press. details

  32. Atiya Masood and Yi Mei and Gang Chen2 and Mengjie Zhang. Many-Objective Genetic Programming for Job-Shop Scheduling. In Yew-Soon Ong editor, Proceedings of 2016 IEEE Congress on Evolutionary Computation (CEC 2016), pages 209-216, Vancouver, 2016. IEEE Press. details