- Vaisi, B., Farughi, H., & Raissi, S. (2018). Two-machine robotic cell sequencing under different uncertainties. Int. J. Simul. Model, 17, 284-294. https://doi.org/10.2507/IJSIMM17(2)434
- Vaisi, B., Farughi, H., & Raissi, S. (2018). Bi-criteria robotic cell scheduling and operation allocation in the presence of break-downs. International journal of industrial engineering & production research, 29(3), 343-357..
- Gultekin, H., Coban, B., & Akhlaghi, V. E. (2018). Cyclic scheduling of parts and robot moves in m-machine robotic cells. Computers & operations research, 90, 161-172. https://doi.org/10.1016/j.cor.2017.09.018
- Yildiz, S., Akturk, M. S., & Karasan, O. E. (2011). Bicriteria robotic cell scheduling with controllable processing times. International Journal of Production Research, 49(2), 569-583. https://doi.org/10.1080/00207540903491799
- Saedi, F., & Kianfar, K. (2023). Scheduling Cellular Manufacturing Systems Based on Human Factors and Due Date of Orders. Journal of Industrial Engineering Research in Production Systems, 10(21), 51-69. doi: 10.22084/ier.2023.27096.210. (in Persian).
- Moradi, V., Yousefi Nejad Attari, M., & Farughi, H. (2018). Modeling for Minimizing Cycle Time in a three-Machine Robotic Cell with Assumption of Tool Switching. Journal of Industrial Engineering Research in Production Systems, 6(12), 1-17. doi: 10.22084/ier.2017.12669.1578. (in Persian).
- Sethi, S.P. , Sriskandarajah, C. , Sorger, G. , Blazewicz, J. , Kubiak, W. (1992) . Sequencing of parts and robot moves in a robotic cell. Int. J. Flexible Manuf. Syst. 4 (3–4), 331–358. https://doi.org/10.1007/BF01324886
- Kats, V., & Levner, E. (1997). A strongly polynomial algorithm for no-wait cyclic robotic flowshop scheduling. Operations Research Letters, 21(4), 171-179. https://doi.org/10.1016/S0167-6377(97)00036-9
- Hall, N. G., Kamoun, H., & Sriskandarajah, C. (1997). Scheduling in robotic cells: classification, two and three machine cells. Operations Research, 45(3), 421-439. https://doi.org/10.1287/opre.45.3.421
- Crama, Y., & Van De Klundert, J. (1997). Cyclic scheduling of identical parts in a robotic cell. Operations Research, 45(6), 952-965. https://doi.org/10.1287/opre.45.6.952
- Levner, E., Kats, V., & Levit, V. E. (1997). An improved algorithm for cyclic flowshop scheduling in a robotic cell. European Journal of Operational Research, 97(3), 500-508. https://doi.org/10.1016/S0377-2217(96)00272-X
- Brauner, N., & Finke, G. (2001). Cycles and permutations in robotic cells. Mathematical and Computer Modelling, 34(5-6), 565-591. https://doi.org/10.1016/S0895-7177(01)00084-X
- Kats, V., Levner, E., & Meyzin, L. (1999). Multiple-part cyclic hoist scheduling using a sieve method. IEEE Transactions on Robotics and Automation, 15(4), 704-713. https://doi.org/10.1109/70.781993
- Che, A., Zhou, Z., Chu, C., & Chen, H. (2011). Multi-degree cyclic hoist scheduling with time window constraints. International journal of production research, 49(19), 5679-5693. https://doi.org/10.1080/00207543.2010.503200
- Zhou, Z., Che, A., & Yan, P. (2012). A mixed integer programming approach for multi-cyclic robotic flowshop scheduling with time window constraints. Applied Mathematical Modelling, 36(8), 3621-3629. https://doi.org/10.1016/j.apm.2011.10.032
- Li, X., & Fung, R. Y. (2014). A mixed integer linear programming solution for single hoist multi-degree cyclic scheduling with reentrance. Engineering Optimization, 46(5), 704-723. https://doi.org/10.1080/0305215X.2013.795560
- Elmi, A., & Topaloglu, S. (2016). Multi-degree cyclic flow shop robotic cell scheduling problem: Ant colony optimization. Computers & Operations Research, 73, 67-83. https://doi.org/10.1016/j.cor.2016.03.007
- Lee, J. H., & Kim, H. J. (2022). Reinforcement learning for robotic flow shop scheduling with processing time variations. International Journal of Production Research, 60(7), 2346-2368. https://doi.org/10.1080/00207543.2021.1887533
- Che, A., Kats, V., & Levner, E. (2017). An efficient bicriteria algorithm for stable robotic flow shop scheduling. European Journal of Operational Research, 260(3), 964-971. https://doi.org/10.1016/j.ejor.2017.01.033
- Kumar, S., Ramanan, N., & Sriskandarajah, C. (2005). Minimizing cycle time in large robotic cells. IIE Transactions, 37(2), 123-136 https://doi.org/10.1080/07408170590885279
- Joo, Y. J. (2009). Operational optimization of an automated electrical die sorting line with single-wafer transfer. Master's thesis, Korea Advanced Institute of Science and Technology.
- Wu, N., & Zhou, M. (2011). Schedulability analysis and optimal scheduling of dual-arm cluster tools with residency time constraint and activity time variation. IEEE Transactions on Automation Science and Engineering, 9(1), 203-209. https://doi.org/10.1109/TASE.2011.2160452
- Kim, H. J., Lee, J. H., & Lee, T. E. (2013). Noncyclic scheduling of cluster tools with a branch and bound algorithm. IEEE Transactions on Automation Science and Engineering, 12(2), 690-700. https://doi.org/10.1109/TASE.2013.2293552
- Wu, X., Yuan, Q., & Wang, L. (2020). Multiobjective differential evolution algorithm for solving robotic cell scheduling problem with batch-processing machines. IEEE transactions on automation science and engineering, 18(2), 757-775. https://doi.org/10.1109/TASE.2020.2969469
- Vaisi, B., Farughi, H., & Raissi, S. (2020). Schedule-allocate and robust sequencing in three-machine robotic cell under breakdowns. Mathematical problems in engineering, 2020, 1-24. https://doi.org/10.1155/2020/4597827
- Kim, H. J., & Lee, J. H. (2021). Scheduling of dual-gripper robotic cells with reinforcement learning. IEEE transactions on automation science and engineering, 19(2), 1120-1136. https://doi.org/10.1109/TASE.2020.3047924
- Zahrouni, W., & Kamoun, H. (2021). Scheduling in robotic cells with time window constraints. European journal of industrial engineering, 15(2), 206-225. https://doi.org/10.1504/EJIE.2021.114001
- Ghadiri Nejad, M., Shavarani, S. M., Vizvári, B., & Barenji, R. V. (2018). Trade-off between process scheduling and production cost in cyclic flexible robotic cells. The international journal of advanced manufacturing technology, 96, 1081-1091. https://doi.org/10.1007/s00170-018-1577-x
- Wang, Z., Zhou, B., Trentesaux, D., & Bekrar, A. (2017). Approximate optimal method for cyclic solutions in multi-robotic cell with processing time window. Robotics and autonomous systems, 98, 307-316. https://doi.org/10.1016/j.robot.2017.09.020
- Majumder, A., & Laha, D. (2016). A new cuckoo search algorithm for 2-machine robotic cell scheduling problem with sequence-dependent setup times. Swarm and evolutionary computation, 28, 131-143. https://doi.org/10.1016/j.swevo.2016.02.001
- Dawande, M., Geismar, H. N., Sethi, S. P., & Sriskandarajah, C. (2005). Sequencing and scheduling in robotic cells: Recent developments. Journal of Scheduling, 8(5), 387-426. https://doi.org/10.1007/s10951-005-2861-9
- Geismar, H. N., & Pinedo, M. (2010). Robotic cells with stochastic processing times. IIE Transactions, 42(12), 897-914. https://doi.org/10.1080/0740817X.2010.491505
- Kim, J. H., & Lee, T. E. (2008). Schedulability analysis of time-constrained cluster tools with bounded time variation by an extended Petri net. IEEE Transactions on Automation Science and Engineering, 5(3), 490-503. https://doi.org/10.1109/TASE.2007.912716
- Yoon, H. J., & Lee, D. Y. (2003, October). On-line scheduling of robotic cells with post-processing residency constraints. In SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme-System Security and Assurance (Cat. No. 03CH37483) (Vol. 3, pp. 2785-2790). IEEE. https://doi.org/10.1109/ICSMC.2003.1244307
- Tonke, D., Grunow, M., & Akkerman, R. (2019). Robotic-cell scheduling with pick-up constraints and uncertain processing times. IISE Transactions, 51(11), 1217-1235. https://doi.org/10.1080/24725854.2018.1555727
- Foumani, M., Razeghi, A., & Smith-Miles, K. (2020). Stochastic optimization of two-machine flow shop robotic cells with controllable inspection times: From theory toward practice. Robotics and Computer-Integrated Manufacturing, 61, 101822. https://doi.org/10.1016/j.rcim.2019.101822
- Vaisi, B. A. H. A. R. E. H., Farughi, H., & Raissi, S. (2020). Multi-Objective Optimal Model for Task Scheduling and Allocation in a Two Machines Robotic Cell Considering Breakdowns. WSEAS transactions on information science and applications, 17, 1-8. https://doi.org/10.37394/23209.2020.17.a025103-920
- Vaisi, B., Farughi, H., & Raissi, S. (2021). Utilization of response surface methodology and goal programming based on simulation in a robotic cell to optimize sequencing. Journal of quality engineering and management, 10(4), 327-338.
- Vaisi, B., Farughi, H., Raissi, S., & Sadeghi, H. (2023). A bi-objective optimal task scheduling model for two-machine robotic-cell subject to probable machine failures. Journal of applied research on industrial engineering, 10(1), 141-154.
- Jalali, Arash and Gholami, Saideh, 2018, Mathematical modeling of m-machine and k-unit robotic cell problem in workshop flow environment, 16th International Industrial Engineering Conference, Tehran.
- Rahmani, D. (2017). A new proactive-reactive approach to hedge against uncertain processing times and unexpected machine failures in the two-machine flow shop scheduling problems. scientia Iranica, 24(3), 1571-1584. https://doi.org/10.24200/sci.2017.4136
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