Abstract
In this paper, we devoted a design of a four-echelon supply chain network including multiple suppliers, multiple plants, multiple distributors and multiple customers. The proposed model is a multi-objective mixed integer linear programming which takes into account several constraints and aims to minimize the total costs including the procurement, production, storage and distribution costs as well as maximize on-time deliveries. Interactive fuzzy goal programming (IFGP) based three different aggregation functions with respect of the structure of supply chain mainly centralized and decentralized is applied to handling multiple objectives and to address the imprecise nature of decision-makers’ aspiration levels for goals. Finally, numerical results are reported for real case study to demonstrate the efficiency and applicability of the proposed model.
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References
Agrawal, V., Ülkü, S.: The role of product modularity in green product design. Manufact. Serv. Oper. Manage. Forthcoming (2012)
Bandyopadhyay, S., Bhattacharya, R.: Solving a tri-objective supply chain problem with modified NSGA-II algorithm. J. Manufact. Syst. 33(1), 41–50 (2014)
Chan, A.T.L., Ngai, E.W.T., Moon, K.K.L.: The effects of strategic and manufacturing flexibilities and supply chain agility on firm performance in the fashion industry. Euro. J. Oper. Res. 259(2), 486–499 (2017)
Díaz-Madroñero, M., Peidro, D., Mula, J.: A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain. Appl. Math. Model. 38(23), 5705–5725 (2014)
Fri, M., Douaioui, K., Lamii, N., Mabrouki, C., Semma, E.A.: A DEA-based hybrid framework to evaluate the performance of port container. In: Advances in Intelligent Systems and Computing, pp. 1–12. Springer International Publishing (2020)
Fri, M., Douaioui, K., Lamii, N., Mabrouki, C., Semma, E.A.: Evaluate the performance of port container using an hybrid framework. In: Embedded Systems and Artificial Intelligence, pp. 517–531. Springer Singapore (2020)
Fri, M., Douaioui, K., Lamii, N., Mabrouki, C., Semma, E.A.: A hybrid framework for evaluating the performance of port container terminal operations. Pomorstvo 34(2), 261–269 (2020)
Fri, M., Douaioui, K., Mabrouki, C., El Alami, S.: Reducing inconsistency in performance analysis for container terminals. Int. J. Supply Oper. Manage. 8(3–4), 328–346 (2021)
Fri, M., Douaioui, K., Tetouani, S., Mabrouki, C., Semma, E.A.: A DEA-ANN framework based in improved grey wolf algorithm to evaluate the performance of container terminal. IOP Conf. Ser. Mater. Sci. Eng. 827, 012040 (2020)
Guillén, G., Mele, F.D., Bagajewicz, M.J., Espuna, A., Puigjaner, L.: Multiobjective supply chain design under uncertainty. Chem. Eng. Sci. 60(6), 1535–1553 (2005)
Gumus, A.T., Guneri, A.F., Keles, S.: Supply chain network design using an integrated neuro-fuzzy and MILP approach: a comparative design study. Expert Syst. Appl. 36(10), 12570–12577 (2009)
Cengiz, K., Oztaysi, B.: Supply Chain Management Under Fuzziness. Springer (2014)
Lambert, D.M., Enz, M.G.: Issues in supply chain management: progress and potential. Ind. Mark. Manage. 62, 1–16 (2017)
Melo, M.T., Nickel, S., Saldanha-Da-Gama, F.: Facility location and supply chain management–a review. Eur. J. Oper. Res. 196(2), 401–412 (2009)
Mirzapour Al-E-Hashem, S.M.,Malekly, H., Aryanezhad, M.B.: A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty. Int. J. Product. Econ. 134(1), 28–42 (2011)
Peidro, D., Mula, J., Jiménez, M., Botella, M.: A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment. Eur. J. Oper. Res. 205(1), 65–80 (2010)
Peidro, D., Mula, J., Poler, R., Lario, F.-C.: Quantitative models for supply chain planning under uncertainty: a review. Int. J. Adv. Manufact. Technol. 43(3–4), 400–420 (2009)
Pishvaee, M.S., Rabbani, M., Torabi, S.A.: A robust optimization approach to closed-loop supply chain network design under uncertainty. Appl. Math. Model. 35(2), 637–649 (2011)
Qi, Y., Huo, B., Wang, Z., Yeung, H.Y.J.: The impact of operations and supply chain strategies on integration and performance. Int. J. Product. Econ. 185, 162–174 (2017)
Santoso, T., Ahmed, S., Goetschalckx, M., Shapiro, A.: A stochastic programming approach for supply chain network design under uncertainty. Eur. J. Oper. Res. 167(1), 96–115 (2005)
Selim, H., Ozkarahan, I.: A supply chain distribution network design model: an interactive fuzzy goal programming-based solution approach. Int. J. Adv. Manufact. Technol. 36(3–4), 401–418 (2008)
Shahabi, M., Akbarinasaji, S., Unnikrishnan, A., James, R.: Integrated inventory control and facility location decisions in a multi-echelon supply chain network with hubs. Netw. Spat. Econ. 13(4), 497–514 (2013)
Shankar, B.L., Basavarajappa, S., Chen, J.C.H., Kadadevaramath, R.S.: Location and allocation decisions for multi-echelon supply chain network–a multi-objective evolutionary approach. Expert Syst. Appl. 40(2), 551–562 (2013)
Tiwari, R.N., Dharmar, S., Rao, J.R.: Fuzzy goal programming-an additive model. Fuzzy Sets Syst. 24(1), 27–34 (1987)
Torabi, S.A., Hassini, E.: Multi-site production planning integrating procurement and distribution plans in multi-echelon supply chains: an interactive fuzzy goal programming approach. Int. J. Product. Res. 47(19), 5475–5499 (2009)
Tsao, Y.-C., Jye-Chyi, L.: A supply chain network design considering transportation cost discounts. Transp. Res. Part Logistics Transp. Rev. 48(2), 401–414 (2012)
Werners, B.: An interactive fuzzy programming system. Fuzzy Sets Syst. 23(1), 131–147 (1987)
Wilhelm, M.M., Blome, C., Bhakoo, V., Paulraj, A.: Sustainability in multi-tier supply chains: understanding the double agency role of the first-tier supplier. J. Oper. Manage. 41, 42–60 (2016)
Zhang, D.Z., et al.: An integrated production and inventory model for a whole manufacturing supply chain involving reverse logistics with finite horizon period. Omega 41(3), 598–620 (2013)
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Douaioui, K., Fri, M., Mabrouki, C., Semma, E.A. (2022). A Multiobjective Integrated Procurement, Production, and Distribution Problem of Supply Chain Network. In: Kacprzyk, J., Balas, V.E., Ezziyyani, M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2020). AI2SD 2020. Advances in Intelligent Systems and Computing, vol 1418. Springer, Cham. https://doi.org/10.1007/978-3-030-90639-9_83
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DOI: https://doi.org/10.1007/978-3-030-90639-9_83
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