۱۶٫ Hosseinian, A.H., and Baradaran, V., (2019), “Detecting communities of workforces for a multi-skill resource-constrained plan scheduling problem: A dandelion resolution approach”, Journal of Industrial and Systems Engineering, Vol. 12, Special emanate on Project Management and Control, 72-99.
۱۷٫ Hartmann, S., (2013). “Project Scheduling with Resource Capacities and Requests Varying with Time: A Case Study”, Flexible Services And Manufacturing Journal, Vol. 25, No. 1, PP. 74-93.
۱۸٫ Pargar F., Zandieh, M., Kauppila, O., and Kujala, J., (2018). “The Effect of Worker Learning on Scheduling Jobs in a Hybrid Flow Shop: A Bi-Objective Approach”, Journal of Systems Science and Systems Engineering, Vol. 27, No. 3, PP. 265-291.
۱۹٫ Najafi, A. A., and Arjmand, M., (2016). “Three Developed Meta-Heuristic Algorithms to Solve RACP Minimizing Makespan and Total Resource Costs Simultaneously”, Journal of Industrial Engineering, Vol. 50, No. 3, PP. 471-482.
۲۰٫ Amin Tahmasbi, H., Daghbandan, A., and Bagherpour, R., (2017). “Dual-Objective Preemptive Multi-Mode Resource-Constrained Project Scheduling Problem Optimization Model”, Journal of Industrial Engineering, Vol. 51, No. 1, PP. 29-44.
۲۱٫ Murata, T., and Ishibuchi, H., (1995). “MOGA: Multi-Objective Genetic Algorithms”, Proceedings of 1995 IEEE International Conference on Evolutionary Computation, Perth, WA, Australia, PP. 289-294.
۲۲٫ Gadhvi, B., Savsani, V., and Patel, V., (2016). “Multi-Objective Optimization of Vehicle Passive Suspension System Using NSGA-II, SPEA2 And PESA-II”, Procedia Technology, Vol. 23, PP. 361-368. DOI: https://doi.org/10.1016/j.protcy.2016.03.038.
۲۳٫ Rahmati, S. H. A., Hajipour, V., and Niaki, S. T. A., (2013). “A Soft-Computing Pareto-Based Meta-Heuristic Algorithm for a Multi-Objective Multi-Server Facility Location Problem”, Applied Soft Computing, Vol. 13, No. 4, PP. 1728-1740.
۲۴٫ Gao, J., Chen, R., and Deng, W., (2013), “An Efficient Tabu Search Algorithm for a Distributed Permutation Flowshop Scheduling Problem”, International Journal of Production Research, Vol. 51, No. 3, PP. 641-651