Fangfang Zhang
Orcid: 0000-0001-5516-3972Affiliations:
- Victoria University of Wellington, Department of Computer Science, New Zealand
According to our database1,
Fangfang Zhang
authored at least 41 papers
between 2018 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Bridging directed acyclic graphs to linear representations in linear genetic programming: a case study of dynamic scheduling.
Genet. Program. Evolvable Mach., June, 2024
Genetic Programming and Reinforcement Learning on Learning Heuristics for Dynamic Scheduling: A Preliminary Comparison.
IEEE Comput. Intell. Mag., May, 2024
Survey on Genetic Programming and Machine Learning Techniques for Heuristic Design in Job Shop Scheduling.
IEEE Trans. Evol. Comput., February, 2024
2023
Task Relatedness-Based Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling.
IEEE Trans. Evol. Comput., December, 2023
Instance-Rotation-Based Surrogate in Genetic Programming With Brood Recombination for Dynamic Job-Shop Scheduling.
IEEE Trans. Evol. Comput., October, 2023
IEEE Trans. Serv. Comput., 2023
Multitask Multiobjective Genetic Programming for Automated Scheduling Heuristic Learning in Dynamic Flexible Job-Shop Scheduling.
IEEE Trans. Cybern., 2023
Sample-Aware Surrogate-Assisted Genetic Programming for Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling.
Proceedings of the Genetic and Evolutionary Computation Conference, 2023
An Investigation of Terminal Settings on Multitask Multi-objective Dynamic Flexible Job Shop Scheduling with Genetic Programming.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023
Multi-Objective Genetic Programming based on Decomposition on Evolving Scheduling Heuristics for Dynamic Scheduling.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023
Proceedings of the Genetic and Evolutionary Computation Conference, 2023
Proceedings of the Genetic and Evolutionary Computation Conference, 2023
Interpretability-Aware Multi-Objective Genetic Programming for Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling.
Proceedings of the IEEE Congress on Evolutionary Computation, 2023
A Semantic Genetic Programming Approach to Evolving Heuristics for Multi-objective Dynamic Scheduling.
Proceedings of the AI 2023: Advances in Artificial Intelligence, 2023
2022
Collaborative Multifidelity-Based Surrogate Models for Genetic Programming in Dynamic Flexible Job Shop Scheduling.
IEEE Trans. Cybern., 2022
Multitask Genetic Programming-Based Generative Hyperheuristics: A Case Study in Dynamic Scheduling.
IEEE Trans. Cybern., 2022
Phenotype Based Surrogate-Assisted Multi-objective Genetic Programming with Brood Recombination for Dynamic Flexible Job Shop Scheduling.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022
A Further Investigation to Improve Linear Genetic Programming in Dynamic Job Shop Scheduling.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022
Importance-Aware Genetic Programming for Automated Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022
Genetic programming with diverse partner selection for dynamic flexible job shop scheduling.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022
An Investigation of Multitask Linear Genetic Programming for Dynamic Job Shop Scheduling.
Proceedings of the Genetic Programming - 25th European Conference, 2022
Learning Strategies on Scheduling Heuristics of Genetic Programming in Dynamic Flexible Job Shop Scheduling.
Proceedings of the IEEE Congress on Evolutionary Computation, 2022
Genetic Programming with Multi-case Fitness for Dynamic Flexible Job Shop Scheduling.
Proceedings of the IEEE Congress on Evolutionary Computation, 2022
Proceedings of the IEEE Congress on Evolutionary Computation, 2022
A Novel Fitness Function for Genetic Programming in Dynamic Flexible Job Shop Scheduling.
Proceedings of the IEEE Congress on Evolutionary Computation, 2022
Proceedings of the IEEE Congress on Evolutionary Computation, 2022
2021
Surrogate-Assisted Evolutionary Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling.
IEEE Trans. Evol. Comput., 2021
Correlation Coefficient-Based Recombinative Guidance for Genetic Programming Hyperheuristics in Dynamic Flexible Job Shop Scheduling.
IEEE Trans. Evol. Comput., 2021
Evolving Scheduling Heuristics via Genetic Programming With Feature Selection in Dynamic Flexible Job-Shop Scheduling.
IEEE Trans. Cybern., 2021
Proceedings of the IEEE Congress on Evolutionary Computation, 2021
Springer, ISBN: 978-981-16-4858-8, 2021
2020
A preliminary approach to evolutionary multitasking for dynamic flexible job shop scheduling via genetic programming.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020
Genetic Programming with Adaptive Search Based on the Frequency of Features for Dynamic Flexible Job Shop Scheduling.
Proceedings of the Evolutionary Computation in Combinatorial Optimization, 2020
Guided Subtree Selection for Genetic Operators in Genetic Programming for Dynamic Flexible Job Shop Scheduling.
Proceedings of the Genetic Programming - 23rd European Conference, 2020
2019
A two-stage genetic programming hyper-heuristic approach with feature selection for dynamic flexible job shop scheduling.
Proceedings of the Genetic and Evolutionary Computation Conference, 2019
A New Representation in Genetic Programming for Evolving Dispatching Rules for Dynamic Flexible Job Shop Scheduling.
Proceedings of the Evolutionary Computation in Combinatorial Optimization, 2019
Evolving Dispatching Rules for Multi-objective Dynamic Flexible Job Shop Scheduling via Genetic Programming Hyper-heuristics.
Proceedings of the IEEE Congress on Evolutionary Computation, 2019
Can Stochastic Dispatching Rules Evolved by Genetic Programming Hyper-heuristics Help in Dynamic Flexible Job Shop Scheduling?
Proceedings of the IEEE Congress on Evolutionary Computation, 2019
2018
Proceedings of the AI 2018: Advances in Artificial Intelligence, 2018
Genetic Programming with Multi-tree Representation for Dynamic Flexible Job Shop Scheduling.
Proceedings of the AI 2018: Advances in Artificial Intelligence, 2018