یزدانی، مهدی؛ زندیه، مصطفی؛ توکلی مقدم؛ رضا (1393). «یک الگوریتم فرا ابتکاری ترکیبی برای مسئله زمانبندی کار کارگاهی منعطف با منابع دوگانه محدود انسان و ماشین». فصلنامه مطالعات مدیریت صنعتی، 12(33)، 74-43.
Andrade-Pineda, J. L., Canca, D., Gonzalez-R, P. L., & Calle, M. Scheduling a dual-resource flexible job shop with makespan and due date-related criteria. Annals of Operations Research, 1-31.
Bartal, Y., Leonardi, S., Marchetti-Spaccamela, A., Sgall, J., & Stougie, L. (2000). Multiprocessor scheduling with rejection. SIAM Journal on Discrete Mathematics, 13(1), 64-78.
Cordone, R., & Hosteins, P. (2019). A bi-objective model for the single-machine scheduling problem with rejection cost and total tardiness minimization. Computers & Operations Research, 102, 130-140.
Dabiri, M., Darestani, S. A., & Naderi, B. (2019). Multi-machine flow shop scheduling problems with rejection using genetic algorithm. International Journal of Services and Operations Management, 32(2), 158-172.
Dudek, R. A., Panwalkar, S. S., & Smith, M. L. (1992). The lessons of flowshop scheduling research. Operations Research, 40(1), 7-13.
Emami, S., Sabbagh, M., & Moslehi, G. (2016). A Lagrangian relaxation algorithm for order acceptance and scheduling problem: a globalised robust optimisation approach. International Journal of Computer Integrated Manufacturing, 29(5), 535-560.
Esmaeilbeigi, R., Charkhgard, P., & Charkhgard, H. (2016). Order acceptance and scheduling problems in two-machine flow shops: new mixed integer programming formulations. European Journal of Operational Research, 251(2), 419-431.
Framinan, J. M., Leisten, R., & García, R. R. (2014). Manufacturing scheduling systems. An integrated view on Models, Methods and Tools, 51-63.
Figielska, E. (2018). Scheduling in a two-stage flowshop with parallel unrelated machines at each stage and shared resources. Computers & Industrial Engineering, 126, 435-450.
Geramipour, S., Moslehi, G., & Reisi-Nafchi, M. (2017). Maximizing the profit in customer’s order acceptance and scheduling problem with weighted tardiness penalty. Journal of the Operational Research Society, 68(1), 89-101.
Gupta, J. N. (1988). Two-stage, hybrid flowshop scheduling problem. Journal of the operational Research Society, 39(4), 359-364.
Gao, L., & Pan, Q. K. (2016). A shuffled multi-swarm micro-migrating birds optimizer for a multi-resource-constrained flexible job shop scheduling problem. Information Sciences, 372, 655-676.
Gong, G., Chiong, R., Deng, Q., Han, W., Zhang, L., Lin, W., & Li, K. (2019). Energy-efficient flexible flow shop scheduling with worker flexibility. Expert Systems with Applications, 112902.
Gong, X., Deng, Q., Gong, G., Liu, W., & Ren, Q. (2018). A memetic algorithm for multi-objective flexible job-shop problem with worker flexibility. International Journal of Production Research, 56(7), 2506-2522.
Johnson, S. M. (1954). Optimal two‐and three‐stage production schedules with setup times included. Naval research logistics quarterly, 1(1), 61-68.
Jan, D., & W Patrick, N. (2009). Ergonomics contributions to company strategies. Applied Ergonomics, 40, 745-752.
Lin, S. W., & Ying, K. C. (2015). Order acceptance and scheduling to maximize total net revenue in permutation flowshops with weighted tardiness. Applied Soft Computing, 30, 462-474.
Lei, D., & Guo, X. (2015). A parallel neighborhood search for order acceptance and scheduling in flow shop environment. International Journal of Production Economics, 165, 12-18.
Li, J., Huang, Y., & Niu, X. (2016). A branch population genetic algorithm for dual-resource constrained job shop scheduling problem. Computers & Industrial Engineering, 102, 113-131.
Lin, H. T., & Liao, C. J. (2003). A case study in a two-stage hybrid flow shop with setup time and dedicated machines. International Journal of Production Economics, 86(2), 133-143.
Lei, D., & Guo, X. (2014). Variable neighbourhood search for dual-resource constrained flexible job shop scheduling. International Journal of Production Research, 52(9), 2519-2529.
Montgomery, D. C. (2005). Design and Analysis of Experiments, Six Edition, John Wiley&Sons.
Mehravaran, Y., & Logendran, R. (2013). Non-permutation flowshop scheduling with dual resources. Expert Systems with Applications, 40(13), 5061-5076.
Meng, L., Zhang, C., Zhang, B., & Ren, Y. (2019). Mathematical Modeling and Optimization of Energy-Conscious Flexible Job Shop Scheduling Problem With Worker Flexibility. IEEE Access.
Naderi, B., Gohari, S., & Yazdani, M. (2014). Hybrid flexible flowshop problems: Models and solution methods. Applied Mathematical Modelling, 38(24), 5767-5780.
Nguyen S, Zhang M, Johnston M (2014) Enhancing branch-and-bound algorithms for order acceptance and scheduling with genetic programming. In: Nicolau M, Krawiec K, Heywood MI, Castelli M, Garcia-Sanchez P, Merelo JJ, Rivas Santos VM, Sim K (eds) Genetic programming, 1st edn. Springer, Berlin, pp 124–136
Nguyen, S., Zhang, M., Johnston, M. (2014) A sequential genetic programming method to learn forward construction heuristics for order acceptance and scheduling. In: 2014 IEEE Congress on Evolutionary Computation (CEC). IEEE, pp. 1824–1831.
- Mohsen, M. Iraj, Multi-job lot streaming to minimize the weighted completion time in a hybrid flow shop scheduling problem with work shift constraint, International Journal of Advanced Manufacturing Technology, 70 (2014) 501-514.
Pan, Q. K., Gao, L., Li, X. Y., & Gao, K. Z. (2017). Effective metaheuristics for scheduling a hybrid flowshop with sequence-dependent setup times. Applied Mathematics and Computation, 303, 89-112.
Pan, Q. K., Ruiz, R., & Alfaro-Fernández, P. (2017). Iterated search methods for earliness and tardiness minimization in hybrid flowshops with due windows. Computers & Operations Research, 80, 50-60.
Pan, Q. K., Wang, L., Li, J. Q., & Duan, J. H. (2014). A novel discrete artificial bee colony algorithm for the hybrid flowshop scheduling problem with makespan minimisation. Omega, 45, 42-56.
Pan, Q. K., Wang, L., Mao, K., Zhao, J. H., & Zhang, M. (2012). An effective artificial bee colony algorithm for a real-world hybrid flowshop problem in steelmaking process. IEEE Transactions on Automation Science and Engineering, 10(2), 307-322.
Quadt, D., & Kuhn, H. (2005). Conceptual framework for lot-sizing and scheduling of flexible flow lines. International Journal of Production Research, 43(11), 2291-2308.
Ruiz, R., & Vázquez-Rodríguez, J. A. (2010). The hybrid flow shop scheduling problem. European journal of operational research, 205(1), 1-18.
Ruiz, R., & Maroto, C. (2006). A genetic algorithm for hybrid flowshops with sequence dependent setup times and machine eligibility. European Journal of Operational Research, 169(3), 781-800.
Silva, Y. L. T., Subramanian, A., & Pessoa, A. A. (2018). Exact and heuristic algorithms for order acceptance and scheduling with sequence-dependent setup times. Computers & Operations Research, 90, 142-160.
Shabtay, D., & Gasper, N. (2012). Two-machine flow-shop scheduling with rejection. Computers & Operations Research, 39(5), 1087-1096.
Shahvari, O., & Logendran, R. (2017). A bi-objective batch processing problem with dual-resources on unrelated-parallel machines. Applied Soft Computing, 61, 174-192.
Silva, Y. L. T., Subramanian, A., & Pessoa, A. A. (2018). Exact and heuristic algorithms for order acceptance and scheduling with sequence-dependent setup times. Computers & Operations Research, 90, 142-160.
Thevenin, S., Zufferey, N., & Widmer, M. (2015). Metaheuristics for a scheduling problem with rejection and tardiness penalties. Journal of Scheduling, 18(1), 89-105.
Thevenin, S., Zufferey, N., & Widmer, M. (2016). Order acceptance and scheduling with earliness and tardiness penalties. Journal of Heuristics, 22(6), 849-890.
Thevenin, S., & Zufferey, N. (2019). Learning Variable Neighborhood Search for a scheduling problem with time windows and rejections. Discrete Applied Mathematics, 261, 344-353.
Udo, G. G., & Ebiefung, A. A. (1999). Human factors affecting the success of advanced manufacturing systems. Computers & Industrial Engineering, 37, 297-300.
Wang J., Zhuang X., Wu B. (2017) A New Model and Method for Order Selection Problems in Flow-Shop Production. In: Choi TM., Gao J., Lambert J., Ng CK., Wang J. (eds) Optimization and Control for Systems in the Big-Data Era. International Series in Operations Research & Management Science, vol 252. Springer, Cham
Wang, S., & Ye, B. (2019). Exact methods for order acceptance and scheduling on unrelated parallel machines. Computers & Operations Research, 104, 159-173.
Wang, S., & Ye, B. (2019). Exact methods for order acceptance and scheduling on unrelated parallel machines. Computers & Operations Research, 104, 159-173.
Waldherr, S., & Knust, S. (2017). Decomposition algorithms for synchronous flow shop problems with additional resources and setup times. European Journal of Operational Research, 259(3), 847-863.
Xu, L., Wang, Q., & Huang, S. (2015). Dynamic order acceptance and scheduling problem with sequence-dependent setup time. International Journal of Production Research, 53(19), 5797-5808.
Xiao, Y., Yuan, Y., Zhang, R. Q., & Konak, A. (2015). Non-permutation flow shop scheduling with order acceptance and weighted tardiness. Applied Mathematics and Computation, 270, 312-333.
Xie, X., & Wang, X. (2016). An enhanced ABC algorithm for single machine order acceptance and scheduling with class setups. Applied Soft Computing, 44, 255-266.
Xiao, Y., Yuan, Y., Zhang, R. Q., & Konak, A. (2015). Non-permutation flow shop scheduling with order acceptance and weighted tardiness. Applied Mathematics and Computation, 270, 312-333.
Yavari, M., Marvi, M. & Akbari, A.H. (2019). Semi-permutation-based genetic algorithm for order acceptance and scheduling in two-stage assembly problem. Neural Comput & Applic doi:10.1007/s00521-019-04027-w
Yazdani, M., Zandieh, M., & Tavakkoli-Moghaddam, R. (2019). Evolutionary algorithms for multi-objective dual-resource constrained flexible job-shop scheduling problem. OPSEARCH, 1-24.
Yu, C., Semeraro, Q., & Matta, A. (2018). A genetic algorithm for the hybrid flow shop scheduling with unrelated machines and machine eligibility. Computers & Operations Research, 100, 211-229.
Zhang, B., Pan, Q. K., Gao, L., Zhang, X. L., Sang, H. Y., & Li, J. Q. (2017). An effective modified migrating birds optimization for hybrid flowshop scheduling problem with lot streaming. Applied Soft Computing, 52, 14-27.
Zohali, H., Naderi, B., & Mohammadi, M. (2019). The economic lot scheduling problem in limited-buffer flexible flow shops: Mathematical models and a discrete fruit fly algorithm. Applied Soft Computing, 80, 904-919.
Zhang, J., Wang, W., & Xu, X. (2017). A hybrid discrete particle swarm optimization for dual-resource constrained job shop scheduling with resource flexibility. Journal of Intelligent Manufacturing, 28(8), 1961-1972.
Zheng, X. L., & Wang, L. (2016). A knowledge-guided fruit fly optimization algorithm for dual resource constrained flexible job-shop scheduling problem. International Journal of Production Research, 54(18), 5554-5566.