Design and Implementation of Sustainable Supply Chain Model with Various Distribution Channels

  • YoungSu YunEmail author
  • Anudari Chuluunsukh
  • Mitsuo Gen
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1002)


In this paper, we propose a sustainable supply chain (SSC) model with various distribution channels. For constructing the SSC model, (1) the minimization of total cost as economic issue, (2) the minimization of total amount of CO\(_2\) emission as environmental issue, and (3) the maximization of total social influence as social issue are considered. Since the SSC model should have various distribution channels, (1) normal delivery, (2) direct delivery, and (3) direct shipment are also taken into consideration in it. A mathematical formulation is proposed to design the SSC model and it is implemented using hybrid genetic algorithm (pro-HGA) approach. In numerical experiments, several scales of the SSC model are presented and they are used to compare the performance of the pro-HGA approach with those of some conventional GA and HGA approaches. Experimental results prove that the pro-HGA approach is more efficient in solving the SSC model than the other competing approaches.


Sustainable supply chain model Economic Environmental and social issues Distribution channel Hybrid genetic algorithm approach Genetic algorithms 


  1. 1.
    Chen, X., Chuluunsukh, A., Yun, Y.S.: Design of closed-loop supply chain model with various transportation methods. In: Proceedings of APIEMS (Asia Pacific Industrial Engineering and Management Systems) Conference: pp. 18–23 (2017)Google Scholar
  2. 2.
    Arampantzi, C., Minis, I.: A new model for designing sustainable supply chain networks and its application to a global manufacturer. J. Clean. Prod. 156, 276–292 (2017)CrossRefGoogle Scholar
  3. 3.
    Barbosa-Póvoa, A.P., da Silva, C., Carvalho, A.: Opportunities and challenges in sustainable supply chain: An operations research perspective. Eur. J. Oper. Res. 268(2), 399–431 (2018)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Chiang, W.K., Monahan, G.E.: Managing inventories in a two-echelon dual-channel supply chain. Eur. J. Oper. Res. 162(2), 325–341 (2005)CrossRefGoogle Scholar
  5. 5.
    Chiang, W.K., Chhajed, D., Hess, J.D.: Direct marketing, indirect profits: A strategic analysis of dual-channel supply-chain design. Manag. Sci. 49(1), 1–20 (2003)CrossRefGoogle Scholar
  6. 6.
    Devika, K., Jafarian, A., Nourbakhsh, V.: Designing a sustainable closed-loop supply chain network based on triple bottom line approach: A comparison of metaheuristics hybridization techniques. Eur. J. Oper. Res. 235(3), 594–615 (2014)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Gen, M., Cheng, R.: Genetic Algorithms and Engineering Optimization, vol. 7. Wiley, New York (2000)Google Scholar
  8. 8.
    Gen, M., Lin, L., et al.: Recent advances in hybrid priority-based genetic algorithms for logistics and scm network design. Comput. Ind. Eng. 125, 394–412 (2018)CrossRefGoogle Scholar
  9. 9.
    Hua, G., Wang, S., Cheng, T.E.: Price and lead time decisions in dual-channel supply chains. Eur. J. Oper. Res. 205(1), 113–126 (2010)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Ishibuchi, H., Yoshida, T., Murata, T.: Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling. IEEE Trans. Evol. Comput. 7(2), 204–223 (2003)CrossRefGoogle Scholar
  11. 11.
    Kanagaraj, G., Ponnambalam, S., Jawahar, N.: A hybrid cuckoo search and genetic algorithm for reliability-redundancy allocation problems. Comput. Ind. Eng. 66(4), 1115–1124 (2013)CrossRefGoogle Scholar
  12. 12.
    Lin, L., Gen, M., Wang, X.: Integrated multistage logistics network design by using hybrid evolutionary algorithm. Comput. Ind. Eng. 56(3), 854–873 (2009)CrossRefGoogle Scholar
  13. 13.
    Min, H., Ko, H.J., Ko, C.S.: A genetic algorithm approach to developing the multi-echelon reverse logistics network for product returns. Omega 34(1), 56–69 (2006)CrossRefGoogle Scholar
  14. 14.
    Mota, B., Gomes, M.I., et al.: Towards supply chain sustainability: Economic, environmental and social design and planning. J. Clean. Prod. 105, 14–27 (2015)CrossRefGoogle Scholar
  15. 15.
    Özceylan, E., Demirel, N., et al.: A closed-loop supply chain network design for automotive industry in turkey. Comput. Ind. Eng. 113, 727–745 (2017)CrossRefGoogle Scholar
  16. 16.
    Paksoy, T., Bektaş, T., Özceylan, E.: Operational and environmental performance measures in a multi-product closed-loop supply chain. Transp. Res. Part E: Logist. Transp. Rev. 47(4), 532–546 (2011)CrossRefGoogle Scholar
  17. 17.
    Savaskan, R.C., Bhattacharya, S., Van Wassenhove, L.N.: Closed-loop supply chain models with product remanufacturing. Manag. Sci. 50(2), 239–252 (2004)CrossRefGoogle Scholar
  18. 18.
    Talaei, M., Moghaddam, B.F., et al.: A robust fuzzy optimization model for carbon-efficient closed-loop supply chain network design problem: a numerical illustration in electronics industry. J. Clean. Prod. 113, 662–673 (2016)CrossRefGoogle Scholar
  19. 19.
    Taticchi, P., Garengo, P., et al.: A review of decision-support tools and performance measurement and sustainable supply chain management. Int. J. Prod. Res. 53(21), 6473–6494 (2015)CrossRefGoogle Scholar
  20. 20.
    Varsei, M., Polyakovskiy, S.: Sustainable supply chain network design: A case of the wine industry in australia. Omega 66, 236–247 (2017)CrossRefGoogle Scholar
  21. 21.
    Yun, Y.S., Chuluunsukh, A.: Environmentally-friendly supply chain network with various transportation types. J. Glob. Tour. Res. 3(1), 17–24 (2018)Google Scholar
  22. 22.
    Yun, Y.S., Chuluunsukh, A., Chen, X.: Hybrid genetic algorithm for optimizing closed-loop supply chain model with direct shipment and delivery. New Phys.: Sae Mulli 68, 683–692 (2018)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Business AdministrationChosun UniversityGwangjuSouth Korea
  2. 2.Fuzzy Logic Systems Institute and Tokyo University of ScienceFukuokaJapan

Personalised recommendations