An effective knowledge transfer method based on semi-supervised learning for evolutionary optimization

Pasha, 2021, An integrated optimization method for tactical-level planning in liner shipping with heterogeneous ship fleet and environmental considerations, Adv. Eng. Inform., 48, 10.1016/j.aei.2021.101299 Dulebenets, 2021, An adaptive polyploid memetic algorithm for scheduling trucks at a cross-docking terminal, Inf. Sci., 565, 390, 10.1016/j.ins.2021.02.039 Fathollahi-Fard, 2021, Two hybrid meta-heuristic algorithms for a dual-channel closed-loop supply chain network design problem in the tire industry under uncertainty, Adv. Eng. Inform., 50, 10.1016/j.aei.2021.101418 Rodrigues-Jr, 2021, Lig-doctor: Efficient patient trajectory prediction using bidirectional minimal gated-recurrent networks, Inf. Sci., 545, 813, 10.1016/j.ins.2020.09.024 Deb, 2014, Multi-objective optimization, Search methodologies, 403, 10.1007/978-1-4614-6940-7_15 González-Almagro, 2021, Me-meoa/dcc: Multiobjective constrained clustering through decomposition-based memetic elitism, Swarm Evolut. Comput., 66, 10.1016/j.swevo.2021.100939 G. Dhiman, K.K. Singh, M. Soni, A. Nagar, K. Cengiz, Mosoa: A new multi-objective seagull optimization algorithm, Expert Syst. Appl. doi:10.1016/j.eswa.2020.114150. Zhao, 2020, An online-learning-based evolutionary many-objective algorithm, Inf. Sci., 509, 1, 10.1016/j.ins.2019.08.069 Liu, 2020, And: A many-objective evolutionary algorithm with angle-based selection and shift-based density estimation, Inf. Sci., 509, 400, 10.1016/j.ins.2018.06.063 Nouri-Moghaddam, 2021, A novel multi-objective forest optimization algorithm for wrapper feature selection, Expert Syst. Appl., 175 Dhal, 2021, A multi-objective feature selection method using newton’s law based pso with gwo, Appl. Soft Comput., 107 Y. Xue, Y. Tang, X. Xu, J. Liang, F. Neri, Multi-objective feature selection with missing data in classification, IEEE Trans. Emerging Top. Comput. Intell. PP (99) (2021) 1–10. doi:10.1109/TETCI.2021.3074147. T. Dokeroglu, A. Deniz, H.E. Kiziloz, A robust multiobjective harris’ hawks optimization algorithm for the binary classification problem, Knowl.-Based Syst. (1) (2021) 107219. doi:10.1016/j.knosys.2021.107219. Gupta, 2016, Multiobjective multifactorial optimization in evolutionary multitasking, IEEE Trans. Cybern., 47, 1652, 10.1109/TCYB.2016.2554622 Gupta, 2022, Half a dozen real-world applications of evolutionary multitasking, and more, IEEE Comput. Intell. Mag., 17, 49, 10.1109/MCI.2022.3155332 C. Wang, J. Liu, K. Wu, Z. Wu, Solving multi-task optimization problems with adaptive knowledge transfer via anomaly detection, IEEE Trans. Evolut. Comput. doi:10.1109/TEVC.2021.3068157. Feng, 2018, Evolutionary multitasking via explicit autoencoding, IEEE Trans. Cybernet., 49, 3457, 10.1109/TCYB.2018.2845361 Lin, 2020, An effective knowledge transfer approach for multiobjective multitasking optimization, IEEE Trans. Cybern., 51, 3238, 10.1109/TCYB.2020.2969025 Lin, 2019, Multiobjective multitasking optimization based on incremental learning, IEEE Trans. Evol. Comput., 24, 824, 10.1109/TEVC.2019.2962747 H. Chen, H.-L. Liu, F. Gu, K.C. Tan, A multi-objective multitask optimization algorithm using transfer rank, IEEE Trans. Evolut. Comput. doi:10.1109/TEVC.2022.3147568. Xu, 2022, Cultural transmission based multi-objective evolution strategy for evolutionary multitasking, Inf. Sci., 582, 215, 10.1016/j.ins.2021.09.007 Bali, 2020, Cognizant multitasking in multiobjective multifactorial evolution: Mo-mfea-ii, IEEE Trans. Cybern., 51, 1784, 10.1109/TCYB.2020.2981733 Hu, 2022, Multitasking multiobjective optimization based on transfer component analysis, Inf. Sci., 605, 182, 10.1016/j.ins.2022.05.037 Xu, 2022, A novel membrane-inspired evolutionary framework for multi-objective multi-task optimization problems, Inf. Sci., 596, 236, 10.1016/j.ins.2022.03.020 Xu, 2022, Cultural transmission based multi-objective evolution strategy for evolutionary multitasking, Inf. Sci., 582, 215, 10.1016/j.ins.2021.09.007 Li, 2020, Multifactorial optimization via explicit multipopulation evolutionary framework, Inf. Sci., 512, 1555, 10.1016/j.ins.2019.10.066 Chen, 2019, An adaptive archive-based evolutionary framework for many-task optimization, IEEE Trans. Emerging Top. Comput. Intell., 4, 369, 10.1109/TETCI.2019.2916051 Bali, 2017, Linearized domain adaptation in evolutionary multitasking, in, IEEE Congress on Evolutionary Computation (CEC), 2017, 1295 X. Xue, K. Zhang, K.C. Tan, L. Feng, J. Wang, G. Chen, X. Zhao, L. Zhang, J. Yao, Affine transformation-enhanced multifactorial optimization for heterogeneous problems, IEEE Trans. Cybern. doi:10.1109/TCYB.2020.3036393. Z. Liang, H. Dong, C. Liu, W. Liang, Z. Zhu, Evolutionary multitasking for multiobjective optimization with subspace alignment and adaptive differential evolution, IEEE Trans. Cybern. doi:10.1109/TCYB.2020.2980888. Chen, 2022, Multi-objective evolutionary multi-tasking algorithm using cross-dimensional and prediction-based knowledge transfer, Inf. Sci., 586, 540, 10.1016/j.ins.2021.12.014 Chen, 2022, Learning task relationships in evolutionary multitasking for multiobjective continuous optimization, IEEE Trans. Cybern., 52, 5278, 10.1109/TCYB.2020.3029176 Gong, 2019, Evolutionary multitasking with dynamic resource allocating strategy, IEEE Trans. Evol. Comput., 23, 858, 10.1109/TEVC.2019.2893614 Wen, 2017, Parting ways and reallocating resources in evolutionary multitasking, in, IEEE Congress on Evolutionary Computation (CEC), 2017, 2404 Yao, 2020, A multiobjective multifactorial optimization algorithm based on decomposition and dynamic resource allocation strategy, Inf. Sci., 511, 18, 10.1016/j.ins.2019.09.058 Li, 2022, Evolutionary competitive multitasking optimization, IEEE Trans. Evol. Comput., 26, 278, 10.1109/TEVC.2022.3141819 Li, 2018, Evolutionary multitasking sparse reconstruction: Framework and case study, IEEE Trans. Evol. Comput., 23, 733, 10.1109/TEVC.2018.2881955 C. Lyu, Y. Shi, L. Sun, C.-T. Lin, Community detection in multiplex networks based on evolutionary multi-task optimization and evolutionary clustering ensemble, IEEE Trans. Evolut. Comput. doi:10.1109/TEVC.2022.3184988. Hanh, 2021, Evolutionary algorithm and multifactorial evolutionary algorithm on clustered shortest-path tree problem, Inf. Sci., 553, 280, 10.1016/j.ins.2020.10.024 Yi, 2020, A multifactorial evolutionary algorithm for multitasking under interval uncertainties, IEEE Trans. Evol. Comput., 24, 908, 10.1109/TEVC.2020.2975381 Sheikhpour, 2017, A survey on semi-supervised feature selection methods, Pattern Recogn., 64, 141, 10.1016/j.patcog.2016.11.003 K. Bennett, A. Demiriz, Semi-supervised support vector machines, Advances in Neural Information processing systems 11. O. Chapelle, B. Scholkopf, A. Zien, Semi-supervised learning (chapelle, o. et al., eds.; 2006)[book reviews], IEEE Trans. Neural Networks 20 (3) (2009) 542–542. Zadeh, 1965, Fuzzy sets, Inform. Control, 8, 338, 10.1016/S0019-9958(65)90241-X Suykens, 1999, Least squares support vector machine classifiers, Neural Process. Lett., 9, 293, 10.1023/A:1018628609742 Deb, 2002, A fast and elitist multiobjective genetic algorithm: Nsga-ii, IEEE Trans. Evolut. Comput., 6, 182, 10.1109/4235.996017 Y. Yuan, Y.-S. Ong, L. Feng, A.K. Qin, A. Gupta, B. Da, Q. Zhang, K.C. Tan, Y. Jin, H. Ishibuchi, Evolutionary multitasking for multiobjective continuous optimization: Benchmark problems, performance metrics and baseline results, arXiv preprint arXiv:1706.02766. L. Feng, K. Qin, A. Gupta, Y. Yuan, Y. Ong, X. Chi, IEEE CEC 2019 competition on evolutionary multi-task optimization, 2019. Y.-F. Li, Z.-H. Zhou, S4vm: safe semi-supervised support vector machine, Tech. rep., 2010. Buche, 2002, Multiobjective evolutionary algorithm for the optimization of noisy combustion processes, IEEE Trans. Syst. Man Cybern. Part C, 32, 460, 10.1109/TSMCB.2002.804372