An automatic multi-objective evolutionary algorithm for the hybrid flowshop scheduling problem with consistent sublots

Ruiz, 2010, The hybrid flow shop scheduling problem, European J. Oper. Res., 205, 1, 10.1016/j.ejor.2009.09.024 Pan, 2017, Effective metaheuristics for scheduling a hybrid flowshop with sequence-dependent setup times, Appl. Math. Comput., 303, 89 Öztop, 2019, Metaheuristic algorithms for the hybrid flowshop scheduling problem, Comput. Oper. Res., 111, 177, 10.1016/j.cor.2019.06.009 Shao, 2020, Modeling and multi-neighborhood iterated greedy algorithm for distributed hybrid flow shop scheduling problem, Knowl-Based Syst., 194, 10.1016/j.knosys.2020.105527 Alfaro-Fernández, 2020, Automatic algorithm design for hybrid flowshop scheduling problems, European J. Oper. Res., 282, 835, 10.1016/j.ejor.2019.10.004 Meng, 2020, More MILP models for hybrid flow shop scheduling problem and its extended problems, Int. J. Prod. Res., 58, 3905, 10.1080/00207543.2019.1636324 Reiter, 1966, A system for managing job-shop production, J. Bus., 371, 10.1086/294867 Wang, 2019, Two-stage hybrid flow shop batching and lot streaming with variable sublots and sequence-dependent setups, Int. J. Prod. Res., 57, 6893, 10.1080/00207543.2019.1571251 Novas, 2019, Production scheduling and lot streaming at flexible job-shops environments using constraint programming, Comput. Ind. Eng., 136, 252, 10.1016/j.cie.2019.07.011 Chang, 2005, A comprehensive review of lot streaming, Int. J. Prod. Res., 43, 1515, 10.1080/00207540412331325396 Cheng, 2013, A review of lot streaming, Int. J. Prod. Res., 51, 7023, 10.1080/00207543.2013.774506 Bozek, 2018, Flexible job shop scheduling with lot streaming and sublot size optimisation, Int. J. Prod. Res., 56, 6391, 10.1080/00207543.2017.1346322 Zhang, 2012, A bare-bones multi-objective particle swarm optimization algorithm for environmental/economic dispatch, Inform. Sci., 192, 213, 10.1016/j.ins.2011.06.004 Zhang, 2016, Fuzzy cost-based feature selection using interval multi-objective particle swarm optimization algorithm, J. Intell. Fuzzy Stst., 31, 2807, 10.3233/JIFS-169162 Han, 2019, Evolutionary multiobjective blocking lot-streaming flow shop scheduling with machine breakdowns, Ieee Trans. Cybern., 49, 184, 10.1109/TCYB.2017.2771213 Dai, 2017, An improvement decomposition-based multi-objective evolutionary algorithm with uniform design, Knowl-Based Syst., 125, 108, 10.1016/j.knosys.2017.03.021 Dong, 2019, An improvement decomposition-based multi-objective evolutionary algorithm using multi-search strategy, Knowl-Based Syst., 163, 572, 10.1016/j.knosys.2018.09.018 López-Ibáñez, 2016, The irace package: Iterated racing for automatic algorithm configuration, Oper. Res. Perspect., 3, 43 Bezerra, 2019, Automatically designing state-of-the-art multi- and many-objective evolutionary algorithms, Evol. Comput., 28, 195, 10.1162/evco_a_00263 Huang, 2020, A survey of automatic parameter tuning methods for metaheuristics, IEEE Trans. Evol. Comput., 24, 201, 10.1109/TEVC.2019.2921598 Pagnozzi, 2019, Automatic design of hybrid stochastic local search algorithms for permutation flowshop problems, European J. Oper. Res., 276, 409, 10.1016/j.ejor.2019.01.018 Zhang, 2020, A three-stage multiobjective approach based on decomposition for an energy-efficient hybrid flow shop scheduling problem, IEEE Trans. Syst. Man Cybern.-S, 50, 4984, 10.1109/TSMC.2019.2916088 Liu, 2008, Single-job lot streaming in m-1 two-stage hybrid flowshops, European J. Oper. Res., 187, 1171, 10.1016/j.ejor.2006.06.066 Cheng, 2016, Two-stage, single-lot, lot streaming problem for a $$1+2$$1+2hybrid flow shop, J. Global Optim., 66, 263, 10.1007/s10898-015-0298-z Zhang, 2003, Model and heuristics for lot streaming of one job in M-1 hybrid flowshops, Int. J. Oper. Quant. Manage., 9, 49 Kim, 1997, Transfer batch scheduling for a two-stage flowshop with identical parallel machines at each stage, OMEGA-Int. J. Manage. Syst., 25, 547, 10.1016/S0305-0483(97)00015-7 Tsubone, 1996, The impact of lot sizing and sequencing on manufacturing performance in a two-stage hybrid flow shop, Int. J. Prod. Res., 34, 3037, 10.1080/00207549608905076 Song, 2013, Batch scheduling problem of hybrid flow shop based on ant colony algorithm, Comput. Integr. Manuf., 19, 1640 Naderi, 2014, A model and imperialist competitive algorithm for hybrid flow shops with sublots and setup times, J. Manuf. Syst., 33, 647, 10.1016/j.jmsy.2014.06.002 Zhang, 2017, An effective modified migrating birds optimization for hybrid flowshop scheduling problem with lot streaming, Appl. Soft. Comput., 52, 14, 10.1016/j.asoc.2016.12.021 Zhang, 2005, Multi-job lot streaming to minimize the mean completion time in m-1 hybrid flowshops, Int. J. Prod. Econ., 96, 189, 10.1016/j.ijpe.2004.04.005 Cheng, 2013, Two-stage, multiple-lot, lot streaming problem for a 1 + 2 hybrid flow shop, IFAC Proc. Vol., 46, 448, 10.3182/20130619-3-RU-3018.00310 Defersha, 2012, Mathematical model and parallel genetic algorithm for hybrid flexible flowshop lot streaming problem, Int. J. Adv. Manuf. Technol., 62, 249, 10.1007/s00170-011-3798-0 Nejati, 2014, Multi-job lot streaming to minimize the weighted completion time in a hybrid flow shop scheduling problem with work shift constraint, Int. J. Adv. Manuf. Technol., 70, 501, 10.1007/s00170-013-5265-6 Lalitha, 2017, Lot streaming in [n-1](1)+n(m) hybrid flow shop, J. Manuf. Syst., 44, 12, 10.1016/j.jmsy.2017.04.018 Nejati, 2016, Lot streaming in a two-stage assembly hybrid flow shop scheduling problem with a work shift constraint, J. Ind. Prod. Eng., 33, 459 Zhang, 2021, A collaborative variable neighborhood descent algorithm for the hybrid flowshop scheduling problem with consistent sublots, Appl. Soft. Comput., 106, 10.1016/j.asoc.2021.107305 Chen, 2020, Multi-objective genetic algorithm for energy-efficient hybrid flow shop scheduling with lot streaming, Ann. Oper. Res., 290, 813, 10.1007/s10479-018-2969-x Li, 2020, Efficient multi-objective algorithm for the lot-streaming hybrid flowshop with variable sub-lots, Swarm. Evol. Comput., 52, 10.1016/j.swevo.2019.100600 Pan, 2014, A novel discrete artificial bee colony algorithm for the hybrid flowshop scheduling problem with makespan minimisation, OMEGA-Int. J. Manage. Syst., 45, 42, 10.1016/j.omega.2013.12.004 Tasgetiren, 2009, A discrete differential evolution algorithm for the single machine total weighted tardiness problem with sequence dependent setup times, Comput. Oper. Res., 36, 1900, 10.1016/j.cor.2008.06.007 Zhang, 2007, MOEA/D: A multiobjective evolutionary algorithm based on decomposition, IEEE Trans. Evol. Comput., 11, 712, 10.1109/TEVC.2007.892759 Zhang, 2019, A multiobjective evolutionary algorithm based on decomposition for hybrid flowshop green scheduling problem, Comput. Ind. Eng., 136, 325, 10.1016/j.cie.2019.07.036 Birattari, 2006, Towards a theory of practice in metaheuristics design: A machine learning perspective, RAIRO-Theor. Inf. Appl., 40, 353, 10.1051/ita:2006009 Balande, 2020, A modified teaching learning metaheuristic algorithm with opposite-based learning for permutation flow-shop scheduling problem, Evol. Intell. Lu, 2019, A multi-objective cellular grey wolf optimizer for hybrid flowshop scheduling problem considering noise pollution, Appl. Soft. Comput., 75, 728, 10.1016/j.asoc.2018.11.043 Deb, 2002, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Trans. Evol. Comput., 6, 182, 10.1109/4235.996017 Lu, 2021, Knowledge-based multi-objective memetic algorithm for green job shop scheduling with variable machining speeds, IEEE. Syst. J.