Integrated optimization of process planning and scheduling problems based on complex networks
Tài liệu tham khảo
Xu, 2020, Industrial information integration - an emerging subject in industrialization and informatization process, J Ind. Inf. Integr., 17
Xu, 2015, 129
Xu, 2016, Inaugural issue editorial, J. Ind. Inf. Integr., 1, 1
Chen, 2016, Industrial information integration—a literature review 2006-2015, J. Ind. Inf. Integr., 2, 30
Chen, 2020, A survey on industrial information integration 2016-2019, J. Ind. Integr. Manag., 5, 33, 10.1142/S2424862219500167
Li, 2021, A real-time information integration framework for multidisciplinary coupling of complex aircrafts - an application of IIIE, J. Ind. Inf. Integr., 22
Ananya, 2022, Resiliency of smart manufacturing enterprises via information integration, J. Ind. Inf. Integr., 28
Zhao, 2022, An ontology self-learning approach for CNC machine capability information integration and representation in cloud manufacturing, J. Ind. Inf. Integr., 25
Xu, 2011, Enterprise systems: state-of-the-art and future trends, IEEE Trans. Industr. Inform., 7, 630, 10.1109/TII.2011.2167156
Terán, 2017, Integration in industrial automation based on multi-agent systems using cultural algorithms for optimizing the coordination mechanisms, Comput. Ind., 91
Manuel, 2022, The integration of smart systems in the context of industrial logistics in manufacturing enterprises, Procedia Comput. Sci., 200
Liu, 2020, A modified genetic algorithm with new encoding and decoding methods for integrated process planning and scheduling problem, IEEE Trans. Cybern., 51, 4429, 10.1109/TCYB.2020.3026651
Xia, 2016, A hybrid genetic algorithm with variable neighborhood search for dynamic integrated process planning and scheduling, Comput. Ind. Eng., 102, 99, 10.1016/j.cie.2016.10.015
Chryssolouris, 1984, Decision making on the factory floor: an integrated approach to process planning and scheduling, Robot. Comput. Integr. Manuf., 1, 315, 10.1016/0736-5845(84)90020-6
Kim, 2003, A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling, Comput. Oper. Res., 30, 1151, 10.1016/S0305-0548(02)00063-1
Meissner, 2019, Implications of cyber-physical production systems on integrated process planning and scheduling, Procedia Manuf., 28, 167, 10.1016/j.promfg.2018.12.027
Varela Maria, 2019, Integrated process planning and scheduling in networked manufacturing systems for I4.0: a review and framework proposal, 27
Lee, 2019, Sustainable integrated process planning and scheduling optimization using a genetic algorithm with an integrated chromosome representation, Sustainability, 11, 502, 10.3390/su11020502
Guo, 2020, Application research of improved genetic algorithm based on machine learning in production scheduling, Neural. Comput. Appl., 32, 1857, 10.1007/s00521-019-04571-5
Zhang, 2020, Multi-objective optimization of integrated process planning and scheduling considering energy savings, Energies, 13, 6181, 10.3390/en13236181
Liu, 2021, Mathematical model and discrete artificial Bee Colony algorithm for distributed integrated process planning and scheduling, J. Manuf. Syst., 61, 300, 10.1016/j.jmsy.2021.09.012
Khettabi, 2022, Sustainable multi-objective process planning in reconfigurable manufacturing environment: adapted new dynamic NSGA-II vs new NSGA-III, Int. J. Prod. Res., 60, 10.1080/00207543.2022.2044537
Bensmaine, 2014, A new heuristic for integrated process planning and scheduling in reconfigurable manufacturing systems, Int. J. Prod. Res., 52, 3583, 10.1080/00207543.2013.878056
Yu, 2018, Dynamic integration of process planning and scheduling using a discrete particle swarm optimization algorithm, Adv. Prod. Eng. Manag., 13, 279
Liu, 2020, A modified genetic algorithm with new encoding and decoding methods for integrated process planning and scheduling problem, IEEE Trans. Cybern.
Cao, 2021, An adaptive multi-strategy artificial bee colony algorithm for integrated process planning and scheduling, IEEE Access, 9, 65622, 10.1109/ACCESS.2021.3075948
Wu, 2021, Two layered approaches integrating harmony search with genetic algorithm for the integrated process planning and scheduling problem, Comput. Ind. Eng., 155, 10.1016/j.cie.2021.107194
Petrovic, 2016, Integration of process planning and scheduling using chaotic particle swarm optimization algorithm, Expert Syst. Appl., 64, 569, 10.1016/j.eswa.2016.08.019
Zhang, 2020, Hierarchical multistrategy genetic algorithm for integrated process planning and scheduling, J. Intell. Manuf., 1
Wen, 2022, Dynamic scheduling method for integrated process planning and scheduling problem with machine fault, Robot. Comput. Integr. Manuf., 77, 10.1016/j.rcim.2022.102334
Watts, 1998, Collective dynamics of ‘small-world’ networks, Nature, 393, 440, 10.1038/30918
Barabási, 1999, Emergence of scaling in random networks, Science, 286, 509, 10.1126/science.286.5439.509
Xuan, 2011, Open shop complex scheduling network model and characteristic analysis, J. Zhejiang Univ. Sci. B, 45, 589
Li, 2020, Robustness of job-shop networks considering order uncertainty, Mach. Des. Manuf., 43
Zhuang, 2019, A heuristic rule based on complex network for open shop scheduling problem with sequence-dependent setup times and delivery times, IEEE Access, 7, 140946, 10.1109/ACCESS.2019.2944296
Freitag, 2015, Dynamics of resource sharing in production networks, CIRP Ann. Manuf. Technol., 64, 435, 10.1016/j.cirp.2015.04.124
Tao, 2017, SDMSim: a manufacturing service supply-demand matching simulator under cloud environment, Robot. Comput. Integr. Manuf., 45, 34, 10.1016/j.rcim.2016.07.001
Zhuang, 2021, Network-based dynamic dispatching rule generation mechanism for real-time production scheduling problems with dynamic job arrivals, Robot. Comput. Integr. Manuf., 73
Marcela, 2021, Ontology network to support the integration of planning and scheduling activities in batch process industries, J. Ind. Inf. Integr., 25
Guo, 2009, Applications of particle swarm optimisation in integrated process planning and scheduling, Robot. Comput. Integr. Manuf., 25, 280, 10.1016/j.rcim.2007.12.002
Deb, 2002, A fast and elitist multi-objective genetic algorithm: NSGA-II, IEEE Trans. Evol. Comput., 6, 182, 10.1109/4235.996017
Guo, 2022, Industrial information integration method to vehicle routing optimization using grey target decision, J. Ind. Inf. Integr., 27