Abstract
In this investigation, a green supply chain (GSC) model has been developed for multi-objective optimization industrial problem. For this purpose, total cost of supply chain and total time including loading and unloading time of materials or products for transportation is minimized. The \(CO_2\) emission cost has been considered for environmental protection concern. Due to vagueness of various data of the proposed model, the parameters of the model have been taken as triangular fuzzy numbers. Expected value technique is used to remove the fuzziness of different parameters. A novel step method has been applied to convert the multi-objectives to a single one. The converted crisp model has been solved by Generalized Reduced Gradient (GRG) technique using LINGO 17.0. A practical numerical experiment with some sensitivity analyses has been carried out to validate the proposed model.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Mendel, J.M.: Uncertain Rule-Based Fuzzy Logic Systems. Introduction and New Directions. Prentice-Hall, Upper Saddle River (2001)
Liu, B., Liu, Y.K.: Expected value of fuzzy variable and fuzzy expected value models. IEEE Trans. Fuzzy Syst. 10, 445–450 (2002)
Tearngy, T., Renayoun, R., de Montgolfier, J., Larichev, O.: Linear programming with multiobjective functions step method (STEM). Math. Program. 1(2), 366–375 (1971)
Sawaragi, Y., Nakayama, H., Tanino, T.: Theory of Multiobjective Optimization. Academic Press, New York (1985)
Shimizu, K.: Theory of Multiobjective and Conflict. Kyoritsu Syuppan, Tokyo (1982). (in Japanese)
Nijkamp, P., Spronk, J.: Interactive multiple goal programming: an evaluation and some results. In: Fandel, G., Gal, T. (eds.) Multiple Criteria Decision Making: Theory and Applications, pp. 278–293. Springer, Berlin (1980)
Spronk, J., Telgen, J.: An ellipsoidal interactive multiple goal programming method. In: Multiple Criteria Decision Making Conference at University of Delware, Newwark, 10–15 August 1980
Choo, E.V., Atkins, D.R.: An interactive algorithm for multiobjective programming. Comput. Oper. Res. 7, 81–88 (1980)
Xu, X., Zhang, W., He, P., Xu, X.: Production and pricing problems in make-to-order supply chain with cap-and-trade regulation. Omega 11(5–6), 389–402 (2015)
Zhu, W., He, Y.: Green product design in supply chains under competition. Eur. J. Oper. Res. 258, 165–180 (2017)
Tanimizua, Y., Amanoa, K.: Integrated production and transportation scheduling for multi-objective green supply chain network design. Procedia CIRP 57, 152–157 (2016)
Sarkis, J.: A strategic decision framework for green supply chain management. J. Clean. Prod. 11, 397–409 (2003)
Elhedhli, S., Merrick, R.: Green supply chain network design to reduce carbon emissions. Transp. Res. Part D 17, 370–379 (2012)
Li, B., Zhu, M., Jiang, Y., Li, Z.: Pricing policies of a competitive dual-channel green supply chain. J. Clean. Prod. 112(3), 2029–2042 (2016)
Uygun, O., Dede, A.: Performance evaluation of green supply chain management using integrated fuzzy multi-criteria decision making techniques. Comput. Ind. Eng. 102, 502–511 (2016)
Liu, P., Yi, S.: Pricing policies of green supply chain considering targeted advertising and product green degree in the big data environment. J. Clean. Prod. 164, 1614–1622 (2017)
Yang, D., Xiao, T.: Pricing and green level decisions of a green supply chain with governmental interventions under fuzzy uncertainties. J. Clean. Prod. 149, 1174–1187 (2017)
Basiri, Z., Heydar, J.: A mathematical model for green supply chain coordination with substitutable products. J. Clean. Prod. 145, 232–249 (2017)
Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–356 (1965)
Pishvaee, M.S., Razm, J.: Environmental supply chain network design using multi-objective fuzzy mathematical programming. Appl. Math. Model. 36(8), 3433–3446 (2012)
Shen, L., Olfat, L., Govindan, K., Khodaverdi, R., Diabat, A.: A fuzzy multi criteria approach for evaluating green supplier’s performance in green supply chain with linguistic preferences. Resour. Conserv. Recycl. 74, 170–179 (2013)
Soleimani, H., Govindan, K., Saghafi, H., Jafari, H.: Fuzzy multi-objective sustainable and green closed-loop supply chain network design. Comput. Ind. Eng. 109, 191–203 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Bera, S., Jana, D.K., Basu, K., Maiti, M. (2020). Novel Multi-objective Green Supply Chain Model with \(CO_2\) Emission Cost in Fuzzy Environment via Soft Computing Technique. In: Castillo, O., Jana, D., Giri, D., Ahmed, A. (eds) Recent Advances in Intelligent Information Systems and Applied Mathematics. ICITAM 2019. Studies in Computational Intelligence, vol 863. Springer, Cham. https://doi.org/10.1007/978-3-030-34152-7_36
Download citation
DOI: https://doi.org/10.1007/978-3-030-34152-7_36
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-34151-0
Online ISBN: 978-3-030-34152-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)