Evolving artificial neural networks using an improved PSO and DPSO J Yu, S Wang, L Xi Neurocomputing 71 (4-6), 1054-1060, 2008 | 269 | 2008 |
Empirical analysis of support vector machine ensemble classifiers S Wang, A Mathew, Y Chen, L Xi, L Ma, J Lee Expert Systems with applications 36 (3), 6466-6476, 2009 | 205 | 2009 |
An effective heuristic for flexible job-shop scheduling problem with maintenance activities S Wang, J Yu Computers & Industrial Engineering 59 (3), 436-447, 2010 | 176 | 2010 |
Bi-objective identical parallel machine scheduling to minimize total energy consumption and makespan S Wang, X Wang, J Yu, S Ma, M Liu Journal of cleaner production 193, 424-440, 2018 | 140 | 2018 |
One-dimensional convolutional auto-encoder-based feature learning for fault diagnosis of multivariate processes S Chen, J Yu, S Wang Journal of Process Control 87, 54-67, 2020 | 132 | 2020 |
Multi-objective optimization of parallel machine scheduling integrated with multi-resources preventive maintenance planning S Wang, M Liu Journal of Manufacturing Systems 37, 182-192, 2015 | 124 | 2015 |
Bi-objective optimization of a single machine batch scheduling problem with energy cost consideration S Wang, M Liu, F Chu, C Chu Journal of cleaner production 137, 1205-1215, 2016 | 113 | 2016 |
A branch and bound algorithm for single-machine production scheduling integrated with preventive maintenance planning S Wang, M Liu International Journal of Production Research 51 (3), 847-868, 2013 | 109 | 2013 |
An energy-efficient two-stage hybrid flow shop scheduling problem in a glass production S Wang, X Wang, F Chu, J Yu International Journal of Production Research 58 (8), 2283-2314, 2020 | 108 | 2020 |
A genetic algorithm for two-stage no-wait hybrid flow shop scheduling problem S Wang, M Liu Computers & Operations Research 40 (4), 1064-1075, 2013 | 96 | 2013 |
A branch-and-bound algorithm for two-stage no-wait hybrid flow-shop scheduling S Wang, M Liu, C Chu International Journal of Production Research 53 (4), 1143-1167, 2015 | 86 | 2015 |
A deep autoencoder feature learning method for process pattern recognition J Yu, X Zheng, S Wang Journal of Process Control 79, 1-15, 2019 | 85 | 2019 |
Two-stage hybrid flow shop scheduling with preventive maintenance using multi-objective tabu search method S Wang, M Liu International Journal of Production Research 52 (5), 1495-1508, 2014 | 85 | 2014 |
A modified support vector data description based novelty detection approach for machinery components S Wang, J Yu, E Lapira, J Lee Applied Soft Computing 13 (2), 1193-1205, 2013 | 84 | 2013 |
A heuristic method for two-stage hybrid flow shop with dedicated machines S Wang, M Liu Computers & Operations Research 40 (1), 438-450, 2013 | 71 | 2013 |
An improved exact algorithm for single-machine scheduling to minimise the number of tardy jobs with periodic maintenance M Liu, S Wang, C Chu, F Chu International Journal of Production Research 54 (12), 3591-3602, 2016 | 59 | 2016 |
Multichannel one-dimensional convolutional neural network-based feature learning for fault diagnosis of industrial processes J Yu, C Zhang, S Wang Neural Computing and Applications 33 (8), 3085-3104, 2021 | 58 | 2021 |
A filtered-beam-search-based heuristic algorithm for flexible job-shop scheduling problem W Shi-Jin, Z Bing-Hai, X Li-Feng International Journal of Production Research 46 (11), 3027-3058, 2008 | 54 | 2008 |
Scheduling on a two-machine permutation flow shop under time-of-use electricity tariffs S Wang, Z Zhu, K Fang, F Chu, C Chu International Journal of Production Research 56 (9), 3173-3187, 2018 | 51 | 2018 |
A comparison between just-in-time and economic order quantity models with carbon emissions S Wang, B Ye Journal of Cleaner Production 187, 662-671, 2018 | 47 | 2018 |