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Research Articles

Optimal planning and scheduling of information processes during interaction among mobile objects

ORCID Icon, ORCID Icon & ORCID Icon
Pages 5905-5924 | Received 29 Dec 2022, Accepted 23 Dec 2023, Published online: 19 Jan 2024

References

  • Alizadeh Bidgoli, Mohsen, and Ali Ahmadian. 2022. “Multi-Stage Optimal Scheduling of Multi-Microgrids Using Deep-Learning Artificial Neural Network and Cooperative Game Approach.” Energy 239:122036. https://doi.org/10.1016/j.energy.2021.122036.
  • Bai, Ruibin, Xinan Chen, Zhi Long Chen, Tianxiang Cui, Shuhui Gong, Wentao He, Xiaoping Jiang, et al. 2021. “Analytics and Machine Learning in Vehicle Routing Research.” International Journal of Production Research 61:4–30. https://doi.org/10.1080/00207543.2021.2013566.
  • Boltyanskii, Vladimir Grigor’evich, Revaz Valer’yanovich Gamkrelidze, and Lev Semenovich Pontryagin. 1960. The Theory of Optimal Processes. i. the Maximum Principle. TRW SPACE TECHNOLOGY LABS LOS ANGELES CALIF.
  • Csalódi, R., Z. Süle, S. Jaskó, T. Holczinger, and J. Abonyi. 2021. “Industry 4.0-Driven Development of Optimization Algorithms: A Systematic Overview.” Complexity 2021:1–22. https://doi.org/10.1155/2021/6621235.
  • Dolgui, Alexandre, Dmitry Ivanov, Suresh P. Sethi, and Boris Sokolov. 2019. “Scheduling in Production, Supply Chain and Industry 4.0 Systems by Optimal Control: Fundamentals, State-of-the-Art and Applications.” International Journal of Production Research 57:411–432. https://doi.org/10.1080/00207543.2018.1442948.
  • Gryaznov, Nikolai Anatol’evich. 2023. “Navigation Data Exchange for Traffic Control.” Informatics and Automation 22 (1): 33–56. https://doi.org/10.15622/ia.22.1.2.
  • Hamann-Lohmer, Jacob, and Rainer Lasch. 2020. “Production Planning and Scheduling in Multi-Factory Production Networks: A Systematic Literature Review.” International Journal of Production Research 59:2028–2054. https://doi.org/10.1080/00207543.2020.1797207.
  • Ivanov, Dmitry.. 2018. “Supply Chain Management and Structural Dynamics Control.” In Structural Dynamics and Resilience in Supply Chain Risk Management. International Series in Operations Research & Management Science. Vol. 265, 1–18. Cham: Springer. https://doi.org/10.1007/978-3-319-69305-7_1.
  • Ivanov, Dmitry, Alexandre Dolgui, and Boris Sokolov. 2022. “Cloud Supply Chain: Integrating Industry 4.0 and Digital Platforms in the ‘Supply Chain-as-a-Service’.” Transportation Research Part E: Logistics and Transportation Review 160:102676. https://doi.org/10.1016/j.tre.2022.102676.
  • Ivanov, Dmitry, Alexandre Dolgui, Boris Sokolov, Frank Werner, and Marina Ivanova. 2016. “A Dynamic Model and an Algorithm for Short-term Supply Chain Scheduling in the Smart Factory Industry 4.0.” International Journal of Production Research 54 (2): 386–402. https://doi.org/10.1080/00207543.2014.999958.
  • Ivanov, Dmitry, Richard Hartl, Alexandre Dolgui, Alexander Pavlov, and Boris Sokolov. 2015. “Integration of Aggregate Distribution and Dynamic Transportation Planning in a Supply Chain with Capacity Disruptions and the Ripple Effect Consideration.” International Journal of Production Research 53 (23): 6963–6979. https://doi.org/10.1080/00207543.2014.986303.
  • Ivanov, D., and B. Sokolov. 2012. “Dynamic Supply Chain Scheduling.” Journal of Scheduling 15 (2): 201–216. https://doi.org/10.1007/s10951-010-0189-6.
  • Ivanov, Dmitry, Boris Sokolov, Weiwei Chen, Alexandre Dolgui, Frank Werner, and Semyon Potryasaev. 2021. “A Control Approach to Scheduling Flexibly Configurable Jobs with Dynamic Structural-Logical Constraints.” IISE Transactions 53 (1): 21–38. https://doi.org/10.1080/24725854.2020.1739787.
  • Ivanov, D., B. Sokolov, F. Werner, and A. Dolgui. 2020. “Proactive Scheduling and Reactive Real-time Control in Industry 4.0.” In Scheduling in Industry 4.0 and Cloud Manufacturing, 11–37. Cham: Springer. https://doi.org/10.1007/978-3-030-43177-8_2
  • Jiang, Zengqiang, Shuai Yuan, Jing Ma, and Qiang Wang. 2021. “The Evolution of Production Scheduling from Industry 3.0 Through Industry 4.0.” International Journal of Production Research 60:3534–3554. https://doi.org/10.1080/00207543.2021.1925772.
  • Ju, SuHeon, and Jong Hun Woo. 2023. “Integration of Long-term Planning and Mid-term Scheduling of Shipbuilding.” Production Planning & Control 34 (6): 524–542. https://doi.org/10.1080/09537287.2021.1940344.
  • Kumar, Sandeep, Bhushan S Purohit, Vikas Manjrekar, Vivek Singh, and Bhupesh Kumar Lad. 2018. “Investigating the Value of Integrated Operations Planning: A Case-based Approach from Automotive Industry.” International Journal of Production Research 56 (22): 6971–6992. https://doi.org/10.1080/00207543.2018.1424367.
  • Liu, Haitao, Zhaoxia Guo, and Zhengzhong Zhang. 2021. “A Hybrid Multi-level Optimisation Framework for Integrated Production Scheduling and Vehicle Routing with Flexible Departure Time.” International Journal of Production Research 59 (21): 6615–6632. https://doi.org/10.1080/00207543.2020.1821927.
  • Liu, Qihao, Xinyu Li, Liang Gao, and Jiaxin Fan. 2022. “Two Novel MILP Models with Different Flexibilities for Solving Integrated Process Planning and Scheduling Problems.” Journal of the Operational Research Society 74:1–13. https://doi.org/10.1080/01605682.2022.2122738.
  • Luo, D., S. Thevenin, and A. Dolgui. 2021. “A Digital Twin-driven Methodology for Material Resource Planning under Uncertainties.” IFIP Advances in Information and Communication Technology 630:321–329. https://doi.org/10.1007/978-3-030-85874-2_34.
  • Ma, Yujie, Gang Du, and Yingying Zhang. 2022. “Dynamic Hierarchical Collaborative Optimisation for Process Planning and Scheduling Using Crowdsourcing Strategies.” International Journal of Production Research 60 (8): 2404–2424. https://doi.org/10.1080/00207543.2021.1892230.
  • Mihoubi, B., B. Bouzouia, and M. Gaham. 2020. “Reactive Scheduling Approach for Solving a Realistic Flexible Job Shop Scheduling Problem.” International Journal of Production Research 59:1–19. https://doi.org/10.1080/00207543.2020.1790686.
  • Nekrasov, A. G., and A. S. Sinitsyna. 2020. “Digital Transformation Infrastructure and Transportation Logistics Systems.” In IOP Conference Series: Materials Science and Engineering 832 (1), https://doi.org/10.1088/1757-899X/832/1/012052.
  • Pavlov, Alexander, Dmitry Ivanov, Dmitry Pavlov, and Alexey Slinko. 2019. “Optimization of Network Redundancy and Contingency Planning in Sustainable and Resilient Supply Chain Resource Management Under Conditions of Structural Dynamics.” Annals of Operations Research, https://doi.org/10.1007/s10479-019-03182-6.
  • Shokouhi, Elahe. 2018. “Integrated Multi-objective Process Planning and Flexible Job Shop Scheduling Considering Precedence Constraints.” Production & Manufacturing Research 6 (1): 61–89. https://doi.org/10.1080/21693277.2017.1415173.
  • Sokolov, B., V. Zakharov, and A. Baranov. 2022. “Combined Models and Algorithms on Modern Proactive Intellectual Scheduling under Industry 4.0 Environment.” IFAC-PapersOnLine 55 (10): 1331–1336. doi:https://doi.org/10.1016/j.ifacol.2022.09.575.
  • Vieira, Miguel, Samuel Moniz, Bruno S Gonçalves, Tânia Pinto-Varela, Ana Paula Barbosa-Póvoa, and Pedro Neto. 2022. “A Two-level Optimisation-Simulation Method for Production Planning and Scheduling: The Industrial Case of a Human–Robot Collaborative Assembly Line.” International Journal of Production Research 60 (9): 2942–2962. https://doi.org/10.1080/00207543.2021.1906461.
  • Yao, Xufeng, Nourah Almatooq, Ronald G Askin, and Greg Gruber. 2022. “Capacity Planning and Production Scheduling Integration: Improving Operational Efficiency via Detailed Modelling.” International Journal of Production Research 60 (24): 7239–7261. https://doi.org/10.1080/00207543.2022.2028031.
  • Zhang, Luping, Chunxia Yu, and T. N. Wong. 2019. “Cloud-based Frameworks for the Integrated Process Planning and Scheduling.” International Journal of Computer Integrated Manufacturing 32 (12): 1192–1206. doi:10.1080/0951192X.2019.1690682.

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