[1] Fangfang Zhang, Yi Mei, and Mengjie Zhang. A new representation in genetic programming for evolving dispatching rules for dynamic flexible job shop scheduling. In Proceedings of the European Conference on Evolutionary Computation in Combinatorial Optimization (EvoCOP), pages 33--49. Springer, apr 2019. [ bib | DOI ]
[2] Fangfang Zhang, Yi Mei, and Mengjie Zhang. Genetic programming with multi-tree representation for dynamic flexible job shop scheduling. In Proceedings of the Australasian Joint Conference on Artificial Intelligence (AI), pages 472--484. Springer, 2018. (Best Paper Runner-Up Award) [ bib | DOI | .pdf ]
[3] Fangfang Zhang, Yi Mei, and Mengjie Zhang. Surrogate-assisted genetic programming for dynamic flexible job shop scheduling. In Proceedings of the Australasian Joint Conference on Artificial Intelligence (AI), pages 766--772. Springer, 2018. [ bib | DOI | .pdf ]
[4] Jordan MacLachlan, Yi Mei, Juergen Branke, and Mengjie Zhang. An improved genetic programming hyper-heuristic for the uncertain capacitated arc routing problem. In Proceedings of the Australasian Joint Conference on Artificial Intelligence (AI), pages 432--444. Springer, 2018. [ bib | DOI | Java Code | .pdf ]
[5] Atiya Masood, Gang Chen, Yi Mei, and Mengjie Zhang. Adaptive reference point generation for many-objective optimization using nsga-iii. In Proceedings of the Australasian Joint Conference on Artificial Intelligence (AI), pages 358--370. Springer, 2018. [ bib | DOI | .pdf ]
[6] John Park, Yi Mei, Su Nguyen, Gang Chen, and Mengjie Zhang. Evolutionary multitask optimisation for dynamic job shop scheduling using niched genetic programming. In Proceedings of the Australasian Joint Conference on Artificial Intelligence (AI), pages 739--751. Springer, 2018. [ bib | DOI | .pdf ]
[7] Mahdi Abdollahi, Xiaoying Gao, Yi Mei, Shameek Ghosh, and Jinyan Li. Uncovering discriminative knowledge-guided medical concepts for classifying coronary artery disease notes. In Proceedings of the Australasian Joint Conference on Artificial Intelligence (AI), pages 104--110. Springer, 2018. [ bib | DOI | .pdf ]
[8] Boxiong Tan, Hui Ma, and Yi Mei. A genetic programming hyper-heuristic approach for online resource allocation in container-based clouds. In Proceedings of the Australasian Joint Conference on Artificial Intelligence (AI), pages 146--152. Springer, 2018. [ bib | DOI | .pdf ]
[9] Deepak Karunakaran, Yi Mei, Gang Chen, and Mengjie Zhang. Sampling heuristics for multi-objective dynamic job shop scheduling using island based parallel genetic programming. In Proceedings of the International Conference on Parallel Problem Solving from Nature (PPSN), pages 347--359. Springer, 2018. [ bib | DOI | .pdf ]
[10] Alexandre Sawczuk da Silva, Hui Ma, Yi Mei, and Mengjie Zhang. A hybrid memetic approach for fully automated multi-objective web service composition. In Proceedings of the IEEE International Conference on Web Services (ICWS), pages 26--33. IEEE, apr 2018. (Best Paper Runner-Up) [ bib | DOI ]
[11] Yi Mei and Mengjie Zhang. Genetic programming hyper-heuristic for multi-vehicle uncertain capacitated arc routing problem. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO), pages 141--142. ACM, jul 2018. [ bib | DOI | Java Code | .pdf ]
[12] Daniel Yska, Yi Mei, and Mengjie Zhang. Feature construction in genetic programming hyper-heuristic for dynamic flexible job shop scheduling. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO), pages 149--150. ACM, jul 2018. [ bib | DOI | .pdf ]
[13] Yi Mei and Mengjie Zhang. Genetic programming hyper-heuristic for stochastic team orienteering problem with time windows. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 1--8. IEEE, jun 2018. [ bib | DOI | Java Code | .pdf ]
[14] Daniel Yska, Yi Mei, and Mengjie Zhang. Genetic programming hyper-heuristic with cooperative coevolution for dynamic flexible job shop scheduling. In Proceedings of the European Conference on Genetic Programming (EuroGP), pages 306--321. Springer, apr 2018. [ bib | DOI | .pdf ]
[15] John Park, Yi Mei, Su Nguyen, Gang Chen, and Mengjie Zhang. Investigating a machine breakdown genetic programming approach for dynamic job shop scheduling. In Proceedings of the European Conference on Genetic Programming (EuroGP), pages 253--270. Springer, apr 2018. [ bib | DOI | .pdf ]
[16] Atiya Masood, Gang Chen, Yi Mei, and Mengjie Zhang. Reference point adaption method for genetic programming hyper-heuristic in many-objective job shop scheduling. In Proceedings of the European Conference on Evolutionary Computation in Combinatorial Optimization (EvoCOP), pages 116--131. Springer, apr 2018. [ bib | DOI | .pdf ]
[17] Yi Mei, Su Nguyen, and Mengjie Zhang. Constrained dimensionally aware genetic programming for evolving interpretable dispatching rules in dynamic job shop scheduling. In Proceedings of the Asia-Pacific Conference on Simulated Evolution and Learning (SEAL), pages 435--447. Springer, 2017. [ bib | DOI | .pdf ]
[18] Yiming Peng, Gang Chen, Mengjie Zhang, and Yi Mei. Effective policy gradient search for reinforcement learning through neat based feature extraction. In Proceedings of the Asia-Pacific Conference on Simulated Evolution and Learning (SEAL), pages 473--485. Springer, 2017. [ bib | DOI ]
[19] Will Hardwick-Smith, Yiming Peng, Gang Chen, Yi Mei, and Mengjie Zhang. Evolving transferable artificial neural networks for gameplay tasks via neat with phased searching. In Proceedings of the Australasian Joint Conference on Artificial Intelligence (AI), pages 39--51. Springer, 2017. [ bib | DOI | .pdf ]
[20] Yuxin Liu, Yi Mei, Mengjie Zhang, and Zili Zhang. Automated heuristic design using genetic programming hyper-heuristic for uncertain capacitated arc routing problem. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pages 290--297. ACM, 2017. [ bib | DOI | .pdf ]
[21] Deepak Karunakaran, Yi Mei, Gang Chen, and Mengjie Zhang. Toward evolving dispatching rules for dynamic job shop scheduling under uncertainty. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pages 282--289. ACM, 2017. [ bib | DOI | .pdf ]
[22] Alexandre Sawczuk da Silva, Yi Mei, Hui Ma, and Mengjie Zhang. Fragment-based genetic programming for fully automated multi-objective web service composition. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pages 353--360. ACM, 2017. [ bib | DOI | .pdf ]
[23] Yiming Peng, Gang Chen, Scott Holdaway, Yi Mei, and Mengjie Zhang. Automated state feature learning for actor-critic reinforcement learning through neat. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pages 135--136. ACM, 2017. [ bib | DOI | .pdf ]
[24] Josiah Jacobsen-Grocott, Yi Mei, Gang Chen, and Mengjie Zhang. Evolving heuristics for dynamic vehicle routing with time windows using genetic programming. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 1948--1955. IEEE, 2017. [ bib | DOI | .pdf ]
[25] Deepak Karunakaran, Yi Mei, Gang Chen, and Mengjie Zhang. Evolving dispatching rules for dynamic job shop scheduling with uncertain processing times. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 364--371. IEEE, 2017. [ bib | DOI | .pdf ]
[26] Boxiong Tan, Hui Ma, and Yi Mei. A nsga-ii-based approach for service resource allocation in cloud. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 2574--2581. IEEE, 2017. [ bib | DOI | .pdf ]
[27] Yi Mei, Su Nguyen, and Mengjie Zhang. Evolving time-invariant dispatching rules in job shop scheduling with genetic programming. In Proceedings of the European Conference on Genetic Programming (EuroGP), pages 147--163. Springer, 2017. [ bib | DOI | Java Code | .pdf ]
[28] Qi Chen, Bing Xue, Yi Mei, and Mengjie Zhang. Geometric semantic crossover with an angle-aware mating scheme in genetic programming for symbolic regression. In Proceedings of the European Conference on Genetic Programming (EuroGP), pages 229--245. Springer, 2017. [ bib | DOI | .pdf ]
[29] Atiya Masood, Yi Mei, Gang Chen, and Mengjie Zhang. A pso-based reference point adaption method for genetic programming hyper-heuristic in many-objective job shop scheduling. In Proceedings of the Australasian Conference on Artificial Life and Computational Intelligence (ACALCI), pages 326--338. Springer, 2017. [ bib | DOI | .pdf ]
[30] John Park, Yi Mei, Su Nguyen, Gang Chen, and Mengjie Zhang. Investigating the generality of genetic programming based hyper-heuristic approach to dynamic job shop scheduling with machine breakdown. In Proceedings of the Australasian Conference on Artificial Life and Computational Intelligence (ACALCI), pages 301--313. Springer, 2017. [ bib | DOI | .pdf ]
[31] Deepak Karunakaran, Yi Mei, Gang Chen, and Mengjie Zhang. Dynamic job shop scheduling under uncertainty using genetic programming. In Proceedings of Intelligent and Evolutionary Systems (IES), pages 195--210. Springer, 2017. [ bib | DOI | .pdf ]
[32] Yi Mei, Mengjie Zhang, and Su Nyugen. Feature selection in evolving job shop dispatching rules with genetic programming. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pages 365--372. ACM, 2016. [ bib | DOI | Java Code | .pdf ]
[33] Yi Mei, Bing Xue, and Mengjie Zhang. Fast bi-objective feature selection using entropy measures and bayesian inference. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pages 469--476. ACM, 2016. [ bib | DOI | Java Code | .pdf ]
[34] John Park, Yi Mei, Gang Chen, and Mengjie Zhang. Niching genetic programming based hyper-heuristic approach to dynamic job shop scheduling: an investigation into distance metrics. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pages 109--110. ACM, 2016. [ bib | DOI | .pdf ]
[35] Yi Mei and Mengjie Zhang. A comprehensive analysis on reusability of gp-evolved job shop dispatching rules. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 3590--3597. IEEE, 2016. [ bib | DOI | .pdf ]
[36] Su Nguyen, Yi Mei, Hui Ma, Aaron Chen, and Mengjie Zhang. Evolutionary scheduling and combinatorial optimisation: Applications, challenges, and future directions. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 3053--3060. IEEE, 2016. [ bib | DOI | .pdf ]
[37] Michael Riley, Yi Mei, and Mengjie Zhang. Improving job shop dispatching rules via terminal weighting and adaptive mutation in genetic programming. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 3362--3369. IEEE, 2016. [ bib | DOI | .pdf ]
[38] Alexandre Sawczuk da Silva, Yi Mei, Hui Ma, and Mengjie Zhang. A memetic algorithm-based indirect approach to web service composition. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2016. [ bib | DOI | .pdf ]
[39] Longfei Yan, Yi Mei, Hui Ma, and Mengjie Zhang. Evolutionary web service composition: A graph-based memetic algorithm. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 201--208. IEEE, 2016. [ bib | DOI | .pdf ]
[40] Atiya Masood, Yi Mei, Gang Chen, and Mengjie Zhang. Many-objective genetic programming for job-shop scheduling. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pages 209--216. IEEE, 2016. [ bib | DOI | .pdf ]
[41] John Park, Yi Mei, Su Nguyen, Gang Chen, Mark Johnston, and Mengjie Zhang. Genetic programming based hyper-heuristics for dynamic job shop scheduling: cooperative coevolutionary approaches. In Proceedings of the European Conference on Genetic Programming (EuroGP), pages 115--132. Springer, 2016. [ bib | DOI | .pdf ]
[42] Boxiong Tan, Yi Mei, Hui Ma, and Mengjie Zhang. Particle swarm optimization for multi-objective web service location allocation. In Proceedings of the European Conference on Evolutionary Computation in Combinatorial Optimization (EvoCOP), pages 219--234. Springer, 2016. [ bib | DOI | .pdf ]
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