بهینه سازی ریاضی برنامه ریزی تولید داده محور بر اساس ویژگی های محیط برنامه ریزی تولید برای ردیابی و تاخیر محصولات در صنعت دارویی بیوفارما

Bueno, A., Filho, M. G., Carvalho, J. V., & Callefi, M. (2022). Smart Production Planning and Control Model. In A. Mesquita, A. Abreu, & J. V. Carvalho (Eds.), Perspectives and Trends in Education and Technology (Vol. 256). Springer, Singapore. https://doi.org/10.1007/978-981-16-5063-5_21

Bueno, A. F., Godinho Filho, M., & Frank, A. G. (2020). Smart production planning and control in the industry 4.0 context: a systematic literature review. Computers & Industrial Engineering, 106774. https://doi.org/10.1016/j.cie.2020.106774

Chien, C. F., & Chen, Y. J. (2022). Data-driven smart manufacturing: Applications, trends and challenges. Journal of Manufacturing Systems, 62, 279-290.

García, E., Hoon Kwak, D., Jeong, Y., & Wiktorsson, M. (2024). Machine learning in smart production logistics: a review of technological capabilities. International Journal of Production Research, 1-35. https://www.researchgate.net/publication/382464697_Machine_learning_in_smart_production_logistics_a_review_of_technological_capabilities

Gomez-Gasquet, P., Boza, A., Perales, D. P., & Esteso, A. (2024). A Deep Reinforcement Learning Approach for Smart Coordination Between Production Planning and Scheduling. In R. Rodríguez-Rodríguez, Y. Ducq, R. D. Leon, & D. Romero (Eds.), Enterprise Interoperability X (Vol. 11). Springer, Cham. https://doi.org/10.1007/978-3-031-24771-2_17

Gupta, A., Singh, R., & Kumar, P. (2020). Data-driven approaches in biopharma production: A review. Biotechnology Advances, 45.

Javaid, W., & Ullah, S. (2025). Data driven simulation based optimization model for job-shop production planning and scheduling: an application in a digital twin shop floor. Journal of Simulation, 1-15. https://doi.org/10.1080/17477778.2025.2469687

Khuat, T. T., McShan, D., & O'Mahony, C. (2023). Machine Learning in Biopharmaceutical Process Development: Current Trends and Future Directions.

Lee, C., Park, J., & Choi, Y. (2022). Data-Driven Multi-Objective Optimization for Sustainable Pharmaceutical Production. Computers & Industrial Engineering, 169, 108141.

Lee, J., Kao, H. A., & Yang, S. (2021). Data-driven smart manufacturing. Journal of Manufacturing Systems, 58, 1-12.

Luo, D., Guan, Z., Ding, L., Fang, W., & Zhu, H. (2025). A Data-Driven Methodology for Hierarchical Production Planning with LSTM-Q Network-Based Demand Forecast. Symmetry, 17(5), 655. https://doi.org/10.3390/sym17050655

Mansouri Mosalou, F., Amiri, M., Taghavi Fard, M. T., & Haji Agha'i Kashteli, M. (2024). Design and Planning of Bioethanol Supply Chain Network with a Hybrid Data-Driven Robust Optimization Approach under Discrete Uncertainty Sets. Decision Making and Operations Research, 327-352. https://www.journal-dmor.ir/article_199979_en.html

Oluyisola, O. E., Bhalla, S., Sgarbossa, F., & Strandhagen, J. O. (2022). Designing and developing smart production planning and control systems in the industry 4.0 era: a methodology and case study. J Intell Manuf, 33, 311-332. https://doi.org/10.1007/s10845-021-01808-w

Oluyisola, O. E., Sgarbossa, F., & Strandhagen, J. O. (2020). Smart Production Planning and Control: Concept, Use-Cases and Sustainability Implications. Sustainability, 12(9), 3791. https://doi.org/10.3390/su12093791

Panjwani, N., Luben, D., Lin, N., Baksh, S., Ultee, M. E., Coffman, J., & Titchener-Hooker, N. J. (2024). Predictive modelling of cell culture performance for commercial biotherapeutics production using historical process data. Biotechnology and Bioengineering. https://doi.org/10.1002/bit.28813

Pascal, G., Tornillo, J. E., Rossit, D. A., & Redchuk, A. (2023). Data-Driven Production Planning and Supply Chain Management: A Brief Review. 2023 4th International Conference on Data Analytics for Business and Industry (ICDABI),

Radmehr, M., Abdollahzadeh Sangarudi, H., & Saheb Jamnia, N. (2020). An Integrated Mathematical Programming Model for Production and Distribution of Radiopharmaceuticals (Case Study: Pars Isotope Company). https://www.magiran.com/paper/2177619/an-integrated-mathematical-model-of-production-and-distribution-planning-for-radiopharmaceutical-products-case-study-pars-isotope-company?lang=en

Razavi. (2022). Optimization of Herbal Drug Production with Genetic Algorithm. Journal of Industrial Engineering of Iran.

Saldanha-da-Gama, F., & Wang, S. (2024). Data-Driven Robust Production Planning. In Facility Location Under Uncertainty (Vol. 356). Springer, Cham. https://doi.org/10.1007/978-3-031-55927-3_16

Sharma, A., Goyal, P., & Choudhary, A. (2021). Biopharmaceutical production: Challenges and recent trends. Biotechnology Reports, 31, e00685.

Su, X., Zeng, L., Shao, B., & Lin, B. (2025). Data-driven optimization for production planning with multiple demand features. Kybernetes, 54(1), 110-133. https://doi.org/10.1108/K-04-2023-0690

Thakur, M., Horst, J., Roth, A., & McNally, D. (2020). Biopharmaceutical production: Planning.

Tripathi, V., Chattopadhyaya, S., Mukhopadhyay, A. K., Saraswat, S., Sharma, S., Li, C., & Georgise, F. B. (2022). A novel smart production management system for the enhancement of industrial sustainability in Industry 4.0. Mathematical Problems in Engineering. https://doi.org/10.1155/2022/6424869

Völker, T., & Mönch, L. (2023). Data-Driven Production Planning Models for Wafer Fabs: An Exploratory Study. IEEE Transactions on Semiconductor Manufacturing, 36(3), 445-457. https://doi.org/10.1109/TSM.2023.3277410

Wang, L. (2023). Data-Driven Modeling Methods for Pharmaceutical Processes. Journal of Pharmaceutical Innovation, 18(1), 112-130.

Wang, S., Yang, G., & Liu, S. (2024). A data-driven multi-channel supply chain multi-factory collaborative production planning problem. Soft Comput. https://doi.org/10.1007/s00500-023-09546-2

Wang, Y., Ma, H., & Zhang, X. (2020). Data-driven production planning for smart manufacturing. Journal of Manufacturing Systems, 54, 321-330.

Zhang, Y., Liu, C., & Lv, J. (2020). Data-driven production planning and scheduling: A review. Journal of Intelligent Manufacturing, 31, 1749-1770.