A Pareto-based collaborative multi-objective optimization algorithm for energy-efficient scheduling of distributed permutation flow-shop with limited buffers

Robotics and Computer-Integrated Manufacturing - Tập 74 - Trang 102277 - 2022
Chao Lu1, Yuanxiang Huang1, Leilei Meng2, Liang Gao3, Biao Zhang2, Jiajun Zhou1
1School of Computer Science, China University of Geosciences, Wuhan 430074, China
2School of Computer Science, Liaocheng University, Liaocheng 252000, China
3State Key Laboratory of Digital Manufacturing Equipment & Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

Tóm tắt

Từ khóa


Tài liệu tham khảo

Naderi, 2010, The distributed permutation flowshop scheduling problem, Comput. Oper. Res., 37, 754, 10.1016/j.cor.2009.06.019

Wang, 2021, Energy-efficient distributed heterogeneous welding flow shop scheduling problem using a modified MOEA/D, Swarm Evol. Comput., 62, 10.1016/j.swevo.2021.100858

Ying, 2018, Minimizing makespan for the distributed hybrid flowshop scheduling problem with multiprocessor tasks, Expert Syst. Appl., 92, 132, 10.1016/j.eswa.2017.09.032

Lu, 2021, Energy-efficient scheduling of distributed flow shop with heterogeneous factories: A real-world case from automobile industry in China, IEEE Trans. Ind. Inf., 17, 6687, 10.1109/TII.2020.3043734

Bargaoui, 2017, A novel chemical reaction optimization for the distributed permutation flowshop scheduling problem with makespan criterion, Comput. Ind. Eng., 111, 239, 10.1016/j.cie.2017.07.020

yao Wang, 2013, An effective estimation of distribution algorithm for solving the distributed permutation flow-shop scheduling problem, Int. J. Prod. Econ., 145, 387, 10.1016/j.ijpe.2013.05.004

Meng, 2019, A distributed permutation flowshop scheduling problem with the customer order constraint, Knowl. Based Syst., 184, 10.1016/j.knosys.2019.104894

Pan, 2019, Effective heuristics and metaheuristics to minimize total flowtime for the distributed permutation flowshop problem, Expert Syst. Appl., 124, 309, 10.1016/j.eswa.2019.01.062

Ruiz, 2019, Iterated Greedy methods for the distributed permutation flowshop scheduling problem, Omega-Int. J. Manage. Sci., 83, 213, 10.1016/j.omega.2018.03.004

Fernandezviagas, 2018, The distributed permutation flow shop to minimise the total flowtime, Comput. Ind. Eng., 118, 464, 10.1016/j.cie.2018.03.014

Lin, 2013, Minimising makespan in distributed permutation flowshops using a modified iterated greedy algorithm, Int. J. Prod. Res., 51, 5029, 10.1080/00207543.2013.790571

Gao, 2011, A hybrid genetic algorithm for the distributed permutation flowshop scheduling problem, Int. J. Comput. Intell. Syst., 4, 497

Fu, 2019, Stochastic multi-objective modelling and optimization of an energy-conscious distributed permutation flow shop scheduling problem with the total tardiness constraint, J. Cleaner Prod., 226, 515, 10.1016/j.jclepro.2019.04.046

Shao, 2020, Modeling and multi-neighborhood iterated greedy algorithm for distributed hybrid flow shop scheduling problem, Knowl. Based Syst., 10.1016/j.knosys.2020.105527

Cai, 2020, Dynamic shuffled frog-leaping algorithm for distributed hybrid flow shop scheduling with multiprocessor tasks, Eng. Appl. Artif. Intell., 90, 103540, 10.1016/j.engappai.2020.103540

Lei, 2020, Solving distributed two-stage hybrid flowshop scheduling using a shuffled frog-leaping algorithm with memeplex grouping, Eng. Optim., 52, 1461, 10.1080/0305215X.2019.1674295

Wang, 2019, An iterated greedy algorithm for distributed hybrid flowshop scheduling problem with total tardiness minimization, 350

Lin, 2017, A backtracking search hyper-heuristic for the distributed assembly flow-shop scheduling problem, Swarm Evol. Comput., 36, 124, 10.1016/j.swevo.2017.04.007

Shao, 2019, A Pareto-based estimation of distribution algorithm for solving multiobjective distributed no-wait flow-shop scheduling problem with sequence-dependent setup time, IEEE Trans. Autom. Sci. Eng., 16, 1344, 10.1109/TASE.2018.2886303

Shao, 2018, Local search methods for a distributed assembly no-idle flow shop scheduling problem, IEEE Syst. J., 13, 1945, 10.1109/JSYST.2018.2825337

Abdollahpour, 2015, Minimizing makespan for flow shop scheduling problem with intermediate buffers by using hybrid approach of artificial immune system, Appl. Soft Comput., 28, 44, 10.1016/j.asoc.2014.11.022

Li, 2015, Solving the large-scale hybrid flow shop scheduling problem with limited buffers by a hybrid artificial bee colony algorithm, Inform. Sci., 316, 487, 10.1016/j.ins.2014.10.009

Wang, 2020, A knowledge-based cooperative algorithm for energy-efficient scheduling of distributed flow-shop, IEEE Trans. Syst. Man Cybern.: Syst., 50, 1805, 10.1109/TSMC.2017.2788879

Zhang, 2021, A discrete whale swarm algorithm for hybrid flow-shop scheduling problem with limited buffers, Robot. Comput.-Integr. Manuf., 68, 102081, 10.1016/j.rcim.2020.102081

Zhang, 2019, Differential evolution metaheuristics for distributed limited-buffer flowshop scheduling with makespan criterion, Comput. Oper. Res., 108, 33, 10.1016/j.cor.2019.04.002

Lu, 2021, Sustainable scheduling of distributed permutation flow-shop with non-identical factory using a knowledge-based multi-objective memetic optimization algorithm, Swarm Evol. Comput., 60, 100803, 10.1016/j.swevo.2020.100803

Lu, 2017, Energy-efficient permutation flow shop scheduling problem using a hybrid multi-objective backtracking search algorithm, J. Cleaner Prod., 144, 228, 10.1016/j.jclepro.2017.01.011

Li, 2018, An effective multiobjective algorithm for energy-efficient scheduling in a real-life welding shop, IEEE Trans. Ind. Inf., 14, 5400, 10.1109/TII.2018.2843441

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

Zhang, 2020, A three-stage multiobjective approach based on decomposition for an energy-efficient hybrid flow shop scheduling problem, IEEE Trans. Syst. Man Cybern.: Syst., 50, 4984, 10.1109/TSMC.2019.2916088

Zhao, 2020, A two-stage cooperative evolutionary algorithm with problem-specific knowledge for energy-efficient scheduling of no-wait flow-shop problem, IEEE Trans. Cybern., PP

Lei, 2019, A two-phase meta-heuristic for multiobjective flexible job shop scheduling problem with total energy consumption threshold, IEEE Trans. Cybern., 49, 1097, 10.1109/TCYB.2018.2796119

Lu, 2021, A knowledge-based multiobjective memetic algorithm for green job shop scheduling with variable machining speeds, IEEE Syst. J., 1

Mouzon, 2007, Operational methods for minimization of energy consumption of manufacturing equipment, Int. J. Prod. Res., 45, 4247, 10.1080/00207540701450013

Dai, 2013, Energy-efficient scheduling for a flexible flow shop using an improved genetic-simulated annealing algorithm, Robot. Comput.-Integr. Manuf., 29, 418, 10.1016/j.rcim.2013.04.001

Luo, 2013, Hybrid flow shop scheduling considering machine electricity consumption cost, Int. J. Prod. Econ., 146, 423, 10.1016/j.ijpe.2013.01.028

Min, 2019, Multi-objective optimization for energy-efficient flexible job shop scheduling problem with transportation constraints, Robot. Comput.-Integr. Manuf., 59, 143, 10.1016/j.rcim.2019.04.006

Yuan, 2021, Research on intelligent workshop resource scheduling method based on improved NSGA-II algorithm, Robot. Comput.-Integr. Manuf., 71, 102141, 10.1016/j.rcim.2021.102141

Gao, 2019, Flexible job-shop rescheduling for new job insertion by using discrete jaya algorithm, IEEE Trans. Cybern., 49, 1944, 10.1109/TCYB.2018.2817240

Lu, 2018, Grey wolf optimizer with cellular topological structure, Expert Syst. Appl., 107, 89, 10.1016/j.eswa.2018.04.012

Deb, 2002, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Trans. Evol. Comput., 6, 182, 10.1109/4235.996017

Papadimitriou, 1980, Flowshop scheduling with limited temporary storage, J. Acm, 27, 533, 10.1145/322203.322213

Lu, 2018, A multi-objective approach to welding shop scheduling for makespan, noise pollution and energy consumption, J. Cleaner Prod., 196, 773, 10.1016/j.jclepro.2018.06.137

Han, 2019, Evolutionary multiobjective blocking lot-streaming flow shop scheduling with machine breakdowns, IEEE Trans. Cybern., 49, 184, 10.1109/TCYB.2017.2771213

Zitzler, 2000, Comparison of multiobjective evolutionary algorithms: Empirical results, Evol. Comput., 8, 173, 10.1162/106365600568202

Zitzler, 1999, Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach, IEEE Trans. Evol. Comput., 3, 257, 10.1109/4235.797969

Li, 2008, Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II, IEEE Trans. Evol. Comput., 13, 284, 10.1109/TEVC.2008.925798

Ding, 2016, Carbon-efficient scheduling of flow shops by multi-objective optimization, European J. Oper. Res., 248, 758, 10.1016/j.ejor.2015.05.019