Novel Multi-objective Green Supply Chain Model with CO2 Emission Cost in Fuzzy Environment via Soft Computing Technique

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.

[1]  J. Heydari,et al.  A mathematical model for green supply chain coordination with substitutable products , 2017 .

[2]  Pan Liu,et al.  Pricing policies of green supply chain considering targeted advertising and product green degree in the Big Data environment , 2017 .

[3]  Samir Elhedhli,et al.  Green supply chain network design to reduce carbon emissions , 2012 .

[4]  Hirotaka Nakayama,et al.  Theory of Multiobjective Optimization , 1985 .

[5]  Joseph Sarkis.  A STRATEGIC DECISION FRAMEWORK FOR GREEN SUPPLY CHAIN MANAGEMENT , 2003 .

[6]  Kannan Govindan,et al.  Fuzzy multi-objective sustainable and green closed-loop supply chain network design , 2017, Comput. Ind. Eng..

[7]  R. Benayoun,et al.  Linear programming with multiple objective functions: Step method (stem) , 1971, Math. Program..

[8]  Eng Ung Choo,et al.  An interactive algorithm for multicriteria programming , 1980, Comput. Oper. Res..

[9]  Yian-Kui Liu,et al.  Expected value of fuzzy variable and fuzzy expected value models , 2002, IEEE Trans. Fuzzy Syst..

[10]  Yoshitaka Tanimizu,et al.  Integrated Production and Transportation Scheduling for Multi-objective Green Supply Chain Network Design , 2016 .

[11]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[12]  Jaap Spronk,et al.  An Ellipsoidal Interactive Multiple Goal Programming Method , 1981 .

[13]  Mir Saman Pishvaee,et al.  Environmental supply chain network design using multi-objective fuzzy mathematical programming , 2012 .

[14]  P. He,et al.  Production and pricing problems in make-to-order supply chain with cap-and-trade regulation , 2017 .

[15]  Wenge Zhu,et al.  Green product design in supply chains under competition , 2017, Eur. J. Oper. Res..

[16]  Peter Nijkamp,et al.  Interactive Multiple Goal Programming: An Evaluation and Some Results , 1980 .

[17]  Tiaojun Xiao,et al.  Pricing and green level decisions of a green supply chain with governmental interventions under fuzzy uncertainties , 2017 .

[18]  B. Li,et al.  Pricing policies of a competitive dual-channel green supply chain , 2016 .

[19]  Ali H. Diabat,et al.  A fuzzy multi criteria approach for evaluating green supplier's performance in green supply chain with linguistic preferences , 2013 .

[20]  Özer Uygun,et al.  Performance evaluation of green supply chain management using integrated fuzzy multi-criteria decision making techniques , 2016, Comput. Ind. Eng..