Aghaei, J., Amjady, N. and Shayanfar, H. A. (2011). Multi-objective electricity market clearing considering dynamic security by lexicographic optimization and augmented epsilon constraint method, Applied Soft Computing Journal, Vol. 11(4), pp. 3846–3858.
Aini, N. M., Astofa, H. F. and Rahmawidya, S. (2020). Integrated production scheduling and distribution allocation for multi ‑ products considering sequence ‑ dependent setups : a practical application, Production Engineering. Springer Berlin Heidelberg, Vol. 14(2), pp. 191–206.
Babazadeh, R. and Razmi, J. (2012). A robust stochastic programming approach for agile and responsive logistics under operational and disruption risks, Int. J. Logistics Systems and Management, Vol. 3(4), pp. 458–482.
Badhotiya, G. K., Soni, G. and Mittal, M. L. (2019). Fuzzy multi-objective optimization for multi-site integrated production and distribution planning in two echelon supply chain, The International Journal of Advanced Manufacturing Technology, Vol. 102(1),, pp. 635-645.
Bertazzi, L. and Zappa, O. (2011). Integrating transportation and production : an international study case, Journal of the Operational Research Society. Nature Publishing Group, Vol. 63(7), pp. 920–930.
Bilgen, B. and Ozkarahan, I. (2004). Strategic tactical and operational production-distribution models: a review, International Journal of Technology Management, Vol. 28(2), pp. 151–171.
Chanchaichujit, J., Saavedra-rosas, J. and Kaur, A. (2016). Analysing the impact of restructuring transportation , production and distribution on costs and environment – a case from the Thai Rubber industry, International Journal of Logistics: Research and Applications. Taylor & Francis, pp. 1–17.
Chiandussi, G. Codegone, M., Ferrero, S., and Varesio, F. E. (2012) Comparison of multi-objective optimization methodologies for engineering applications, Computers and Mathematics with Applications. Elsevier Ltd. doi: 10.1016/j.camwa.2011.11.057.
Cóccola, M. E. Zamarripa, M., Méndez, C. A., and Espuña, A (2013). Toward integrated production and distribution management in multi-echelon supply chains, Computers and Chemical Engineering, Vol. 57, pp. 78–94.
Díaz-Madroñero, M., Peidro, D. and Mula, J. (2015). A review of tactical optimization models for integrated production and transport routing planning decisions, Computers and Industrial Engineering, Vol. 88, pp. 518–535.
Ehrgott, M. and Wiecek, M. M. (2005). Multiobjective programming, in : State of the Art Surveys. International Series in Operations Research & Management Science, Vol 78, pp. 668–722.
Entezaminia, A., Heidari, M. and Rahmani, D. (2016). Robust aggregate production planning in a green supply chain under uncertainty considering reverse logistics : a case study, The International Journal of Advanced Manufacturing Technology. Vol. 90(5), pp. 1507-1528.
Fahimnia, B. Farahani, R. Z., Marian, R., & Luong, (2013). A review and critique on integrated production-distribution planning models and techniques, Journal of Manufacturing Systems, Vol. 32(1), pp. 1–19.
Felfel, H., Ayadi, O. and Masmoudi, F. (2016). Analytic hierarchy process-based approach for selecting a Pareto optimal solution of a multi-objective multi-site supply chain planning problem, Engineering Optimization, Vol. 26(5), pp. 885–898.
Goodarzian, F. and Fakhrzad, M. B. (2021). A New Multi-Objective Mathematical Model for A Citrus Supply Chain Network Design : Metaheuristic Algorithms, Journal of Optimization in Industrial Engineering, Vol. 14(2), pp. 111–128.
Govindan, K. and Fattahi, M. (2015). Investigating risk and robustness measures for supply chain network design under demand uncertainty: A case study of glass supply chain, International Journal of Production Economics. Elsevier, Vol. 183, pp. 680–699.
Haimes, Y. Y., Lasdon, L. S. and Wismer, D. A. (1971). On a Bicriterion Formulation of the Problems of Integrated System Identification and System Optimization, IEEE Journals & Magazines, Vol. 47, pp. 296–297.
He, Z., Guo, Z. and Wang, J. (2018). Integrated scheduling of production and distribution operations in a global MTO supply chain, Enterprise Information Systems. Taylor & Francis, pp. 1–25.
Jabbarzadeh, A., Haughton, M. and Pourmehdi, F. (2018). A Robust Optimization Model for Efficient and Green Supply Chain Planning with Postponement Strategy, International Journal of Production Economics. Elsevier B.V., Vol. 59, pp. 1–58.
Kumar, R. Ganapathy, L., Gokhale, R., & Tiwari, M. K. (2020). Quantitative approaches for the integration of production and distribution planning in the supply chain : a systematic literature review, International Journal of Production Research. Taylor & Francis, pp. 1–27.
Lindo Systems INC (2003) Optimization modeling with LINGO.
Liu, S. and Papageorgiou, L. G. (2013). Multiobjective optimisation of production, distribution and capacity planning of global supply chains in the process industry, Omega, Vol. 41(2), pp. 369–382.
Marler, R. T. and Arora, J. S. (2004). Survey of multi-objective optimization methods for engineering, Struct Multidisc Optim, Vol. 26, pp. 369–395. doi: 10.1007/s00158-003-0368-6.
Mavrotas, G. (2009). Effective implementation of the ɛ-constraint method in Multi-Objective Mathematical Programming problems, Applied Mathematics and Computation, Vol. 213(2), pp. 455–465.
Meisel, F., Kirschstein, T. and Bierwirth, C. (2013). Integrated production and intermodal transportation planning in large scale production-distribution-networks, Transportation Research Part E: Logistics and Transportation Review, Vol. 60, pp. 62–78.
Mirzapour Al-E-Hashem, S. M. J. Baboli, A., Sadjadi, S. J., and Aryanezhad, M. B. (2011).A multiobjective stochastic production-distribution planning problem in an uncertain environment considering risk and workers productivity, Mathematical Problems in Engineering, Vol. 2011, pp. 1-14.
Mirzapour Al-E-Hashem, S. M. J., Baboli, A. and Sazvar, Z. (2013). A stochastic aggregate production planning model in a green supply chain: Considering flexible lead times, nonlinear purchase and shortage cost functions, European Journal of Operational Research, Vol. 230(1), pp. 26–41.
Mirzapour Al-E-Hashem, S. M. J., Malekly, H., & Aryanezhad, M. B. (2011). A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty, International Journal of Production Economics,Vol. 134(1), pp. 28–42. doi: 10.1016/j.ijpe.2011.01.027.
Mokhtari, H. and Hasani, A. (2017). A multi-objective model for cleaner production-transportation planning in manufacturing plants via fuzzy goal programming, Journal of Manufacturing Systems. Vol., 44, pp. 230–242.
Nemati, Y. and Hosein, M. (2019). A fuzzy bi-objective MILP approach to integrate sales , production , distribution and procurement planning in a FMCG supply chain, Soft Computing, Vol. 23(13), pp. 4871–4890.
Ngai, E. W. T. Peng, S., Alexander, P., & Moon, K. K. (2014). Decision support and intelligent systems in the textile and apparel supply chain: An academic review of research articles, Expert Systems with Applications, Vol. 41(1), pp. 81–91.
Rafiei, H., Safaei, F. and Rabbani, M. (2018). Integrated production-distribution planning problem in a competition-based four-echelon supply chain, Computers and Industrial Engineering, Vol. 119, pp. 85–99.
Safra, I. and Jebali, A. (2018). Capacity planning in textile and apparel supply chains, IMA Journal of Management Mathematics, Vol. 30(2), pp. 209-233
Sanowar, M. H. and Mosharraf, M. H. (2018). Application of interactive fuzzy goal programming for multi-objective integrated production and distribution planning, Int. J. Process Management and Benchmarking, Vol. 8(1), pp. 35–58.
Sarmiento, A. M. and Nagi, R. (1999). A review of integrated analysis of production- distribution systems, IIE Transactions, Vol. 31(11), pp. 1061–1074.
Thomas, D. J. Griffin, P. (1996). Coordinated supply chain management’, European Journal of Operational Research, Vol. 94(1), pp. 1–15. d
Torabi, S. A. and Hassini, E. (2009). Multi-site production planning integrating procurement and distribution plans in multi-echelon supply chains: An interactive fuzzy goal programming approach, International Journal of Production Research, Vol. 47(19), pp. 5475–5499.
Weskamp, C. Koberstein, A., Schwartz, F., Suhl, L., and Voß, S. (2018). A two-stage stochastic programming approach for identifying optimal postponement strategies in supply chains with uncertain demand, Omega, Vol. 49, pp. 123-138.