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Fangfang Zhang 0003
Person information
- affiliation: Victoria University of Wellington, Department of Computer Science, New Zealand
Other persons with the same name
- Fangfang Zhang — disambiguation page
- Fangfang Zhang 0001
— Chinese Academy of Sciences, Aerospace Information Research Institute, Key Laboratory of Digital Earth Science, Beijing, China
- Fangfang Zhang 0002
- Fangfang Zhang 0004
- Fangfang Zhang 0005 — Pennsylvania State University, Department of Computer Science and Engineering, University Park, PA, USA
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2020 – today
- 2024
- [j14]Meng Xu
Genetic Programming and Reinforcement Learning on Learning Heuristics for Dynamic Scheduling: A Preliminary Comparison. IEEE Comput. Intell. Mag. 19(2): 18-33 (2024) - [j13]Zhixing Huang, Yi Mei, Fangfang Zhang, Mengjie Zhang, Wolfgang Banzhaf:
Bridging directed acyclic graphs to linear representations in linear genetic programming: a case study of dynamic scheduling. Genet. Program. Evolvable Mach. 25(1): 5 (2024) - [j12]Fangfang Zhang
Survey on Genetic Programming and Machine Learning Techniques for Heuristic Design in Job Shop Scheduling. IEEE Trans. Evol. Comput. 28(1): 147-167 (2024) - [j11]Meng Xu
Genetic Programming With Lexicase Selection for Large-Scale Dynamic Flexible Job Shop Scheduling. IEEE Trans. Evol. Comput. 28(5): 1235-1249 (2024) - [j10]Zai-Xing Sun
Multi-Tree Genetic Programming Hyper-Heuristic for Dynamic Flexible Workflow Scheduling in Multi-Clouds. IEEE Trans. Serv. Comput. 17(5): 2687-2703 (2024) - [c35]Luyao Zhu, Fangfang Zhang, Mengyuan Feng, Ke Chen, Xiaodong Zhu, Mengjie Zhang:
Crossover Operators Between Multiple Scheduling Heuristics with Genetic Programming for Dynamic Flexible Job Shop Scheduling. CEC 2024: 1-8 - [c34]Zai-Xing Sun
Evolving Scheduling Heuristics for Energy-Efficient Dynamic Workflow Scheduling in Cloud via Genetic Programming Hyper-Heuristics. ICIC (1) 2024: 169-182 - [i1]Zhixing Huang, Yi Mei, Fangfang Zhang, Mengjie Zhang, Wolfgang Banzhaf:
Multi-Representation Genetic Programming: A Case Study on Tree-based and Linear Representations. CoRR abs/2405.14268 (2024) - 2023
- [j9]Fangfang Zhang
Multitask Multiobjective Genetic Programming for Automated Scheduling Heuristic Learning in Dynamic Flexible Job-Shop Scheduling. IEEE Trans. Cybern. 53(7): 4473-4486 (2023) - [j8]Fangfang Zhang
Instance-Rotation-Based Surrogate in Genetic Programming With Brood Recombination for Dynamic Job-Shop Scheduling. IEEE Trans. Evol. Comput. 27(5): 1192-1206 (2023) - [j7]Fangfang Zhang
Task Relatedness-Based Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling. IEEE Trans. Evol. Comput. 27(6): 1705-1719 (2023) - [j6]Meng Xu
Genetic Programming for Dynamic Workflow Scheduling in Fog Computing. IEEE Trans. Serv. Comput. 16(4): 2657-2671 (2023) - [c33]Meng Xu
A Semantic Genetic Programming Approach to Evolving Heuristics for Multi-objective Dynamic Scheduling. AI (2) 2023: 403-415 - [c32]Gaofeng Shi, Fangfang Zhang, Yi Mei:
Interpretability-Aware Multi-Objective Genetic Programming for Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling. CEC 2023: 1-8 - [c31]Fangfang Zhang
An Investigation of Terminal Settings on Multitask Multi-objective Dynamic Flexible Job Shop Scheduling with Genetic Programming. GECCO Companion 2023: 259-262 - [c30]Luyao Zhu
Sample-Aware Surrogate-Assisted Genetic Programming for Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling. GECCO 2023: 384-392 - [c29]Meng Xu
Multi-Objective Genetic Programming based on Decomposition on Evolving Scheduling Heuristics for Dynamic Scheduling. GECCO Companion 2023: 427-430 - [c28]Zhixing Huang
Grammar-guided Linear Genetic Programming for Dynamic Job Shop Scheduling. GECCO 2023: 1137-1145 - [c27]Jordan MacLachlan
Learning Emergency Medical Dispatch Policies Via Genetic Programming. GECCO 2023: 1409-1417 - 2022
- [j5]Fangfang Zhang
Collaborative Multifidelity-Based Surrogate Models for Genetic Programming in Dynamic Flexible Job Shop Scheduling. IEEE Trans. Cybern. 52(8): 8142-8156 (2022) - [j4]Fangfang Zhang
Multitask Genetic Programming-Based Generative Hyperheuristics: A Case Study in Dynamic Scheduling. IEEE Trans. Cybern. 52(10): 10515-10528 (2022) - [c26]Jordan MacLachlan, Yi Mei
Genetic Programming for Vehicle Subset Selection in Ambulance Dispatching. CEC 2022: 1-8 - [c25]Gaofeng Shi, Fangfang Zhang, Yi Mei
A Novel Fitness Function for Genetic Programming in Dynamic Flexible Job Shop Scheduling. CEC 2022: 1-8 - [c24]Meng Xu, Yi Mei
Genetic Programming with Cluster Selection for Dynamic Flexible Job Shop Scheduling. CEC 2022: 1-8 - [c23]Meng Xu, Fangfang Zhang, Yi Mei
Genetic Programming with Multi-case Fitness for Dynamic Flexible Job Shop Scheduling. CEC 2022: 1-8 - [c22]Fangfang Zhang, Yi Mei
Learning Strategies on Scheduling Heuristics of Genetic Programming in Dynamic Flexible Job Shop Scheduling. CEC 2022: 1-8 - [c21]Zhixing Huang
An Investigation of Multitask Linear Genetic Programming for Dynamic Job Shop Scheduling. EuroGP 2022: 162-178 - [c20]Meng Xu, Yi Mei
Genetic programming with diverse partner selection for dynamic flexible job shop scheduling. GECCO Companion 2022: 615-618 - [c19]Zhixing Huang
Graph-based linear genetic programming: a case study of dynamic scheduling. GECCO 2022: 955-963 - [c18]Fangfang Zhang
Importance-Aware Genetic Programming for Automated Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling. PPSN (2) 2022: 48-62 - [c17]Zhixing Huang, Yi Mei, Fangfang Zhang, Mengjie Zhang:
A Further Investigation to Improve Linear Genetic Programming in Dynamic Job Shop Scheduling. SSCI 2022: 496-503 - [c16]Fangfang Zhang, Yi Mei, Su Nguyen
Phenotype Based Surrogate-Assisted Multi-objective Genetic Programming with Brood Recombination for Dynamic Flexible Job Shop Scheduling. SSCI 2022: 1218-1225 - 2021
- [b1]Fangfang Zhang, Su Nguyen, Yi Mei
Genetic Programming for Production Scheduling - An Evolutionary Learning Approach, 3. Springer 2021, ISBN 978-981-16-4858-8, pp. 3-321 - [j3]Fangfang Zhang
Evolving Scheduling Heuristics via Genetic Programming With Feature Selection in Dynamic Flexible Job-Shop Scheduling. IEEE Trans. Cybern. 51(4): 1797-1811 (2021) - [j2]Fangfang Zhang
Correlation Coefficient-Based Recombinative Guidance for Genetic Programming Hyperheuristics in Dynamic Flexible Job Shop Scheduling. IEEE Trans. Evol. Comput. 25(3): 552-566 (2021) - [j1]Fangfang Zhang
Surrogate-Assisted Evolutionary Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling. IEEE Trans. Evol. Comput. 25(4): 651-665 (2021) - [c15]Meng Xu, Fangfang Zhang, Yi Mei
Genetic Programming with Archive for Dynamic Flexible Job Shop Scheduling. CEC 2021: 2117-2124 - 2020
- [c14]Fangfang Zhang
Guided Subtree Selection for Genetic Operators in Genetic Programming for Dynamic Flexible Job Shop Scheduling. EuroGP 2020: 262-278 - [c13]Fangfang Zhang
Genetic Programming with Adaptive Search Based on the Frequency of Features for Dynamic Flexible Job Shop Scheduling. EvoCOP 2020: 214-230 - [c12]Fangfang Zhang, Yi Mei
A preliminary approach to evolutionary multitasking for dynamic flexible job shop scheduling via genetic programming. GECCO Companion 2020: 107-108
2010 – 2019
- 2019
- [c11]Fangfang Zhang, Yi Mei
Can Stochastic Dispatching Rules Evolved by Genetic Programming Hyper-heuristics Help in Dynamic Flexible Job Shop Scheduling? CEC 2019: 41-48 - [c10]Fangfang Zhang, Yi Mei
Evolving Dispatching Rules for Multi-objective Dynamic Flexible Job Shop Scheduling via Genetic Programming Hyper-heuristics. CEC 2019: 1366-1373 - [c9]Fangfang Zhang, Yi Mei
A New Representation in Genetic Programming for Evolving Dispatching Rules for Dynamic Flexible Job Shop Scheduling. EvoCOP 2019: 33-49 - [c8]Fangfang Zhang, Yi Mei
A two-stage genetic programming hyper-heuristic approach with feature selection for dynamic flexible job shop scheduling. GECCO 2019: 347-355 - 2018
- [c7]Fangfang Zhang
Genetic Programming with Multi-tree Representation for Dynamic Flexible Job Shop Scheduling. Australasian Conference on Artificial Intelligence 2018: 472-484 - [c6]Fangfang Zhang
Surrogate-Assisted Genetic Programming for Dynamic Flexible Job Shop Scheduling. Australasian Conference on Artificial Intelligence 2018: 766-772 - 2016
- [c5]Fangfang Zhang, Li Li, Jing Liu
Artificial Bee Colony Optimization for Yard Truck Scheduling and Storage Allocation Problem. ICIC (2) 2016: 908-917 - [c4]Ben Niu, Jing Liu
A Cooperative Structure-Redesigned-Based Bacterial Foraging Optimization with Guided and Stochastic Movements. ICIC (2) 2016: 918-927 - [c3]Ben Niu, Fangfang Zhang, Li Li, Lang Wu:
Proceedings in Adaptation, Learning and Optimization. IES 2016: 333-346 - [c2]Li Li, Fangfang Zhang
Modified Brain Storm Optimization Algorithms Based on Topology Structures. ICSI (2) 2016: 408-415 - 2015
- [c1]Xiaobing Gan, Lijiao Liu, Ben Niu, Lijing Tan, Fangfang Zhang
SRBFOs for Solving the Heterogeneous Fixed Fleet Vehicle Routing Problem. ICIC (2) 2015: 725-732
Coauthor Index
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