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A Multiobjective Integrated Procurement, Production, and Distribution Problem of Supply Chain Network

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Advanced Intelligent Systems for Sustainable Development (AI2SD’2020) (AI2SD 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1418))

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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

  1. Agrawal, V., Ülkü, S.: The role of product modularity in green product design. Manufact. Serv. Oper. Manage. Forthcoming (2012)

    Google Scholar 

  2. Bandyopadhyay, S., Bhattacharya, R.: Solving a tri-objective supply chain problem with modified NSGA-II algorithm. J. Manufact. Syst. 33(1), 41–50 (2014)

    Article  Google Scholar 

  3. 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)

    Google Scholar 

  4. 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)

    Article  MathSciNet  Google Scholar 

  5. 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)

    Google Scholar 

  6. 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)

    Google Scholar 

  7. 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)

    Google Scholar 

  8. 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)

    Google Scholar 

  9. 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)

    Google Scholar 

  10. 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)

    Article  Google Scholar 

  11. 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)

    Google Scholar 

  12. Cengiz, K., Oztaysi, B.: Supply Chain Management Under Fuzziness. Springer (2014)

    Google Scholar 

  13. Lambert, D.M., Enz, M.G.: Issues in supply chain management: progress and potential. Ind. Mark. Manage. 62, 1–16 (2017)

    Google Scholar 

  14. 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)

    Google Scholar 

  15. 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)

    Google Scholar 

  16. 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)

    Google Scholar 

  17. 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)

    Article  Google Scholar 

  18. 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)

    Google Scholar 

  19. 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)

    Article  Google Scholar 

  20. 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)

    Article  MathSciNet  Google Scholar 

  21. 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)

    Article  Google Scholar 

  22. 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)

    Article  MathSciNet  Google Scholar 

  23. 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)

    Google Scholar 

  24. Tiwari, R.N., Dharmar, S., Rao, J.R.: Fuzzy goal programming-an additive model. Fuzzy Sets Syst. 24(1), 27–34 (1987)

    Article  MathSciNet  Google Scholar 

  25. 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)

    Google Scholar 

  26. 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)

    Article  Google Scholar 

  27. Werners, B.: An interactive fuzzy programming system. Fuzzy Sets Syst. 23(1), 131–147 (1987)

    Article  MathSciNet  Google Scholar 

  28. 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)

    Google Scholar 

  29. 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)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. LMII - Faculty of Sciences and Technology, Hassan 1st University, PO Box 577, Settat, Morocco

    Kaoutar Douaioui, Charif Mabrouki & El Alami Semma

  2. Euromed University of Fes (UEMF)-Fez-Morocco, Fez, Morocco

    Mouhsene Fri

Authors
  1. Kaoutar Douaioui
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  2. Mouhsene Fri
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  3. Charif Mabrouki
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  4. El Alami Semma
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Editor information

Editors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, Warszawa, Poland

    Janusz Kacprzyk

  2. Aurel Vlaicu University of Arad, Arad, Romania

    Valentina E. Balas

  3. Sciences and Techniques of Tangier, Abdelmalek Essaâdi University, Tangier, Morocco

    Mostafa Ezziyyani

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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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