توسعه مدل ریاضی زمان بندی کارگاهی منعطف با در نظر گرفتن محدودیت‌های دوگانه منابع انسانی و ماشین آلات، تاثیر یادگیری و وقفه‌های تولید

[1] Xie, J., Li, X., Gao, L., & Gui, L. (2022). A hybrid algorithm with a new neighborhood structure for job shop scheduling problems. Computers & Industrial Engineering, 169, 108205.

[2] Tang, J., Gong, G., Peng, N., Zhu, K., Huang, D., & Luo, Q. (2024). An effective memetic algorithm for distributed flexible job shop scheduling problem considering integrated sequencing flexibility. Expert Systems with Applications, 242, 122734.

[3] Yuan, M., Huang, H., Li, Z., Zhang, C., Pei, F., & Gu, W. (2023). A multi-agent double deep-Q-network based on state machine and event stream for flexible job shop scheduling problem. Advanced Engineering Informatics, 58, 102230.

[4] Rolf, B., Jackson, I., Müller, M., Lang, S., Reggelin, T., & Ivanov, D. (2023). A review on reinforcement learning algorithms and applications in supply chain management. International Journal of Production Research, 61(20), 7151-7179.

[5] Li, Y., Liao, C., Wang, L., Xiao, Y., Cao, Y., & Guo, S. (2023). A reinforcement learning-artificial bee colony algorithm for flexible job-shop scheduling problem with lot streaming. Applied Soft Computing, 146, 110658.

[6] Kaya, S., Gümüşçü, A., Aydilek, I. B., Karacizmeli, I. H., & Tenekeci, M. E. (2021). Solution for flow shop scheduling problems using chaotic hybrid firefly and particle swarm optimization algorithm with improved local search. Soft Computing, 25(10), 7143-7154.

[7] Kumari, M., De, P. K., Narang, P., & Shah, N. H. (2023). Integrated optimization of inventory, replenishment, and vehicle routing for a sustainable supply chain utilizing a novel hybrid algorithm with carbon emission regulation. Expert Systems with Applications, 220, 119667.

[8] Konovalenko, I., & Ludwig, A. (2022). Generating decision support for alarm processing in cold supply chains using a hybrid k-NN algorithm. Expert Systems with Applications, 190, 116208.

[9] Cáceres-Gelvez, S., Arango-Serna, M. D., & Zapata-Cortes, J. A. (2024). Optimising production scheduling decisions in flowshop manufacturing cells for a sportswear manufacturing case. International Journal of Advanced Operations Management, 15(4), 324-348.

[10] Akl, A. M., El Sawah, S., Chakrabortty, R. K., & Turan, H. H. (2022). A joint optimization of strategic workforce planning and preventive maintenance scheduling: a simulation–Optimization approach. Reliability Engineering & System Safety, 219(1), 108-175.

[11] Do Amaral, J. V. S., Montevechi, J. A. B., de Carvalho Miranda, R., & de Sousa Junior, W. T. (2022). Metamodel-based simulation optimization: A systematic literature review. Simulation Modelling Practice and Theory, 114(1), 102403.

[12] Chen, R., Yang, B., Li, S., & Wang, S. (2020). A self-learning genetic algorithm based on reinforcement learning for flexible job-shop scheduling problem. Computers & Industrial Engineering, 149, 106778.

[13] Sun, J., Zhang, G., Lu, J., & Zhang, W. (2021). A hybrid many-objective evolutionary algorithm for flexible job-shop scheduling problem with transportation and setup times. Computers & Operations Research, 132, 105263.

[14] An, Y., Chen, X., Gao, K., Zhang, L., Li, Y., & Zhao, Z. (2023a). A hybrid multi-objective evolutionary algorithm for solving an adaptive flexible job-shop rescheduling problem with real-time order acceptance and condition-based preventive maintenance. Expert Systems with Applications, 212, 118711.

[15] An, Y., Chen, X., Gao, K., Zhang, L., Li, Y., & Zhao, Z. (2023b). Integrated optimization of real-time order acceptance and flexible job-shop rescheduling with multi-level imperfect maintenance constraints. Swarm and Evolutionary Computation, 77, 101243.

[16] Martins, M. S., Viegas, J. L., Coito, T., Firme, B., Costigliola, A., Figueiredo, J., Sousa, J. M. (2023). Minimizing total completion time in large-sized pharmaceutical quality control scheduling. Journal of Heuristics, 29(1), 177-206.

[17] Pal, M., Mittal, M. L., Soni, G., Chouhan, S. S., & Kumar, M. (2023). A multi-agent system for FJSP with setup and transportation times. Expert Systems with Applications, 216, 119474.