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A fuzzy multi-objective model for supplier selection to mitigate the impact of vehicle transportation gases and delivery time

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Abstract

The evaluation and selection of suppliers is a complicated, multi-objective decision-making task that is influenced by multiple variables. This article presents a multi-objective approach for the problem of selecting a product supplier, in which the total cost—including supplier costs and buyer costs, as well as environmental pollutants that result from vehicle transportation. The pollutant of environment is considered an influential factor in the evaluation and selection of the supplier. The suggested model's objectives include lowering the cost of suppliers (total ordering and shortage costs), minimizing low-quality goods from suppliers, minimizing delivery time, and minimizing the amount of environmental pollutants emitted by vehicles.

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References

  • Abir AS, Ahmed Bhuiyan I, Arani M, Billal MM (2020) Multi-objective optimization for sustainable closed-loop supply Chain network under demand uncertainty: a genetic algorithm. 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), pp 1–5. https://doi.org/10.1109/ICDABI51230.2020.9325648

  • Ahmadini AAH, Modibbo UM, Shaikh AA, Ali I (2021) Multi-objective optimization modelling of sustainable green supply chain in inventory and production management. Alex Eng J 60(6):5129–5146

    Article  Google Scholar 

  • Amid A, Ghodsypour SH, O’Brien Ch (2006) Fuzzy multi-objective linear model for supplierselection in a supply chain. Int J Prod Econ 104:394–407

    Article  Google Scholar 

  • Amid A, Ghodsypour SH, O’Brien Ch (2009) A weighted additive fuzzy multi-objective model forthe supplier selection problem under price breaks in a supply chain" Int J Prod Econ 121:323–332

    Article  Google Scholar 

  • Arabani M, Balooch Sirgani P (2022) Evaluation of performance and moisture sensitivity of polymer-modified mixture containing glass aggregates. Int J Pavement Res Technol 15:1166–1179. https://doi.org/10.1007/s42947-021-00080-8

  • Carlsson C, Fullér R (1994) Interdependence in fuzzy multiple objective programming. Fuzzy Sets Syst 65(1):19–29

    Article  MathSciNet  Google Scholar 

  • Daaboul J, Le Duigou J, Penciuc D et al (2014) Reverse logistics network design: a holistic life cycle approach. Jnl Remanufactur 4:7. https://doi.org/10.1186/s13243-014-0007-y

    Article  Google Scholar 

  • Eslamipoor R (2022) An optimization model for green supply chain by regarding emission tax rate in incongruous vehicles. Model Earth Syst Environ. https://doi.org/10.1007/s40808-022-01470-y

    Article  Google Scholar 

  • Eslamipoor R, Nobari A (2022) A reliable and sustainable design of supply chain in healthcare under uncertainty regarding environmental impacts. J Appl Res Ind Eng. https://doi.org/10.22105/JARIE.2022.335389.1461

  • Fallah-Tafti AL, Sahraeian R, Tavakkoli-Moghaddam R (2014) An interactive possibilistic programming approach for a multi-objective closed-loop supply chain network under uncertainty. Int J Syst Sci 45(3):283–299

    Article  MathSciNet  MATH  Google Scholar 

  • Gao N, Ryan SM (2014) Robust design of a closed-loop supply chain network for uncertain carbon regulations and random product flows. EURO J Transp Logist 3(1):5–34

    Article  Google Scholar 

  • Govindan K, Sivakumar R (2016) Green supplier selection and order allocation in a low-carbon paper industry: integrated multi-criteria heterogeneous decision-making and multi-objective linear programming approaches. Ann Oper Res 238(1):243–276

    Article  MathSciNet  MATH  Google Scholar 

  • Gupta P, Govindan K, Mehlawat MK, Kumar S (2016) A weighted possibilistic programming approach for sustainable vendor selection and order allocation in fuzzy environment. Int J Adv Manuf Technol 86(5):1785–1804

    Article  Google Scholar 

  • Guua SM, Wu YK (1999) Two-phase approach for solving the fuzzy linear programming problems. Fuzzy Sets Syst 107(2):191–195

    Article  MathSciNet  Google Scholar 

  • Hou Y, Khokhar M, Zia S, Sharma A (2022) Assessing the best supplier selection criteria in supply chain management during the COVID-19 pandemic. Front Psychol 12:804954. https://doi.org/10.3389/fpsyg.2021.804954

  • Kumar D, Rahman Z, Chan FTS (2017) A fuzzy AHP and fuzzy multi-objective linear programming model for order allocation in a sustainable supply chain: A case study. Int J Comput Integr Manuf 30(6):535–551

    Article  Google Scholar 

  • Naqvi MA, Amin SH (2021) Supplier selection and order allocation: a literature review. J Data, Inf Manag 3(2):125–139

    Article  Google Scholar 

  • Nayeri S, Paydar MM, Asadi-Gangraj E, Emami S (2020) Multi-objective fuzzy robust optimization approach to sustainable closed-loop supply chain network design. Comput Ind Eng 148:106716

    Article  Google Scholar 

  • Pal Om, Gupta AK, Garg RK (2013) Supplier selection criteria and methods in supply chains: A review. Int J Econ Manag Eng 7(10):2667–2673

    Google Scholar 

  • Pinto F, de Jesus P, dos Santos Grecco CH, Cosenza CAN (2020) Fuzzy model for the priorization analysis of variable quality performance: an approach in shipbuilding. Fuzzy Inf Eng 12(2):181–203

    Article  Google Scholar 

  • Sepehriar A, Eslamipoor R, Nobari A (2013) A new mixed fuzzy-LP method for selecting the best supplier using fuzzy group decision making. Neural Comput Applic 23(1):345–352

  • Tsao Y-C, Thanh V-V, Jye-Chyi Lu, Vincent Yu (2018) Designing sustainable supply chain networks under uncertain environments: Fuzzy multi-objective programming. J Clean Prod 174:1550–1565

    Article  Google Scholar 

  • Uygun Ö, Dede A (2016) Performance evaluation of green supply chain management using integrated fuzzy multi-criteria decision making techniques. Comput Ind Eng 102:502–511

    Article  Google Scholar 

  • Werners BM (1988) Aggregation models in mathematical programming. In: Mitra G (ed) Mathematical Mod- els for Decision Support. Springer, Berlin, pp 295–305

    Chapter  Google Scholar 

  • Xia W, Wu Z (2007) Supplier selection with multiple criteria in volume discount environments. Omega 35(5):494–504

    Article  Google Scholar 

  • Yu J, Gan Mi, Ni S, Chen D (2018) Multi-objective models and real case study for dual-channel FAP supply chain network design with fuzzy information. J Intell Manuf 29(2):389–403

    Article  Google Scholar 

  • Zimmermann HJ (1993) Fuzzy set theory and its applications (2nd Revised ed.). Kluwer Academic Publishers, Boston, Dordrecht, London (6th printing)

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Authors and Affiliations

  1. Faculty of Business and Law, De Montfort University, Leicester, UK

    Reza Eslamipoor

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  1. Reza Eslamipoor
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Correspondence to Reza Eslamipoor.

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Eslamipoor, R. A fuzzy multi-objective model for supplier selection to mitigate the impact of vehicle transportation gases and delivery time. J. of Data, Inf. and Manag. 4, 231–241 (2022). https://doi.org/10.1007/s42488-022-00076-4

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