Fangfang Zhang

PhD Student School of Engineering and Computer Science

Fangfang Zhang profile picture

Thesis Info

Research Interests: Evolutionary Computation, Genetic Programming, Hyper-heuristic, Job Shop Scheduling
Thesis Title: Genetic Programming Hyper-heuristics for Dynamic Flexible Job Shop Scheduling
Supervisor: Dr Yi Mei and Prof Mengjie Zhang

 

Publications

  1. Fangfang Zhang, Yi Mei, and Mengjie Zhang. "A Two-stage Genetic Programming Hyper-heuristic Approach with Feature Selection for Dynamic Flexible Job Shop Scheduling". Accepted by The Genetic and Evolutionary Computation Conference, Prague, Czech Republic, 13-17 July 2019.
  2. Fangfang Zhang, Yi Mei, and Mengjie Zhang. "Can Stochastic Dispatching Rules Evolved by Genetic Programming Hyperheuristics Help in Dynamic Flexible Job Shop Scheduling?". Accepted by 2019 IEEE Congress on Evolutionary Computation (CEC 2019), Wellington, New Zealand, 10-13 June 2019.
  3. Fangfang Zhang, Yi Mei, and Mengjie Zhang. "Evolving Dispatching Rules for Multi-objective Dynamic Flexible Job Shop Scheduling via Genetic Programming Hyper-heuristics ". Accepted by 2019 IEEE Congress on Evolutionary Computation (CEC 2019), Wellington, New Zealand, 10-13 June 2019.
  4. Fangfang Zhang, Yi Mei, and Mengjie Zhang. "A New Representation in Genetic Programming for Evolving Dispatching Rules for Dynamic Flexible Job Shop Scheduling". Proceedings of the 19th European Conference on Evolutionary Computation in Combinatorial Optimization (EvoCOP 2019), Lecture Notes in Computer Science, Vol.11452, Springer. Leipzig, Germany, 24-26 April 2019. pp. 33-49. ISBN: 978-3-030-16711-0
  5. Fangfang Zhang, Yi Mei, and Mengjie Zhang. "Genetic Programming with Multi-tree Representation for Dynamic Flexible Job Shop Scheduling". Proceedings of the 31st Australasian Joint Conference on Artificial Intelligence (AI 2018), Lecture Notes in Computer Science, Vol. 11320, Springer. Wellington, New Zealand, 11-14 December 2018. pp. 472-484. ISBN: 978-3-030-03991-2. (Best Paper Runner-Up Award)
  6. Fangfang Zhang, Yi Mei, and Mengjie Zhang. "Surrogate-Assisted Genetic Programming for Dynamic Flexible Job Shop Scheduling". Proceedings of the 31st Australasian Joint Conference on Artificial Intelligence (AI 2018), Lecture Notes in Computer Science , Vol. 11320, Springer. Wellington, New Zealand, 11-14 December 2018. pp. 766-772. ISBN: 978-3-030-03991-2