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Optimal Design of an Eco-Friendly Transportation Network under Uncertain Parameters

Author

Listed:
  • Ahmad Alshamrani

    (Department of Statistics and Operations Research, College of Sciences, King Saud University, Riyadh 11451, Saudi Arabia)

  • Dipanjana Sengupta

    (School of Management, National Institute of Technology Agartala, Jirania 799046, India)

  • Amrit Das

    (Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore 632014, India)

  • Uttam Kumar Bera

    (Department of Mathematics, National Institute of Technology Agartala, Jirania 799046, India)

  • Ibrahim M. Hezam

    (Department of Statistics and Operations Research, College of Sciences, King Saud University, Riyadh 11451, Saudi Arabia)

  • Moddassir Khan Nayeem

    (Department of Industrial and Production Engineering, Military Institute of Science and Technology, Dhaka 1216, Bangladesh)

  • Faisal Aqlan

    (Industrial Engineering Department, J.B. Speed School of Engineering, University of Louisville, Louisville, KY 40292, USA)

Abstract

The choice of attributes in the multi-attribute decision-making process becomes frequently uncertain because of the diverse degree of preference for alternatives. These are assessed utilizing human decisions and linguistic terms that can be utilized for a more adaptable and delicate assessment. The present article illustrates a multi-attribute decision-making (MADM) process, named the exponential technique for order of preference by similarity to an ideal solution (Exp-TOPSIS), considering the selection of attributes with existing uncertainty. Another three notable multi-attribute decision-making (MADM) processes, termed as multi-attribute utility theory (MAUT), elimination and choice expressing reality method (ELECTRE), and the technique for order of preference by similarity to an ideal solution (TOPSIS) are utilized to present a comparison with the proposed methodology by proposing a mathematical model for a solid transportation problem intending to minimize carbon emissions under an uncertain environment. The uncertainty theory, which depends on human conviction degree, is utilized to define the uncertain parameters of the model related to the problem. Applying the proposed one and the other three multi-attribute decision-making processes, the best emission factors are observed to mitigate the carbon emissions from the transport sectors. In this context, the proposed method has some advantages over the existing techniques in selecting the emission factors. All four MADM approaches with different weights have been tested to choose the best five attributes among nine options to be utilized in the mathematical model to minimize the total carbon emission ejection from transportation. In every case, the obtained result states that the proposed Exp-TOPSIS gives the minimum carbon emissions in a range of 2100–2500 units. LINGO 13.0 solver is used to address the deterministic solid transportation problem, and finally, this study presents some investigations on the selection of carbon emission factors and future utilization of the proposed multi-attribute decision-making process.

Suggested Citation

  • Ahmad Alshamrani & Dipanjana Sengupta & Amrit Das & Uttam Kumar Bera & Ibrahim M. Hezam & Moddassir Khan Nayeem & Faisal Aqlan, 2023. "Optimal Design of an Eco-Friendly Transportation Network under Uncertain Parameters," Sustainability, MDPI, vol. 15(6), pages 1-26, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5538-:d:1103481
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    References listed on IDEAS

    as
    1. Choudhary, Alok & Sarkar, Sagar & Settur, Srikar & Tiwari, M.K., 2015. "A carbon market sensitive optimization model for integrated forward–reverse logistics," International Journal of Production Economics, Elsevier, vol. 164(C), pages 433-444.
    2. Yeh, Chung-Hsing & Chang, Yu-Hern, 2009. "Modeling subjective evaluation for fuzzy group multicriteria decision making," European Journal of Operational Research, Elsevier, vol. 194(2), pages 464-473, April.
    3. Shenle Pan & Eric Ballot & Frédéric Fontane, 2013. "The reduction of greenhouse gas emissions from freight transport by pooling supply chains," Post-Print hal-00733678, HAL.
    4. K. B. Haley, 1962. "New Methods in Mathematical Programming---The Solid Transportation Problem," Operations Research, INFORMS, vol. 10(4), pages 448-463, August.
    5. Soysal, M. & Bloemhof-Ruwaard, J.M. & van der Vorst, J.G.A.J., 2014. "Modelling food logistics networks with emission considerations: The case of an international beef supply chain," International Journal of Production Economics, Elsevier, vol. 152(C), pages 57-70.
    6. Alam, Shahriar Tanvir & Ahmed, Sayem & Ali, Syed Mithun & Sarker, Sudipa & Kabir, Golam & ul-Islam, Asif, 2021. "Challenges to COVID-19 vaccine supply chain: Implications for sustainable development goals," International Journal of Production Economics, Elsevier, vol. 239(C).
    7. Tzeng, Gwo-Hshiung & Lin, Cheng-Wei & Opricovic, Serafim, 2005. "Multi-criteria analysis of alternative-fuel buses for public transportation," Energy Policy, Elsevier, vol. 33(11), pages 1373-1383, July.
    8. M. Dev Anand & T. Selvaraj & S. Kumanan & M. Austin Johnny, 2008. "Application of multicriteria decision making for selection of robotic system using fuzzy analytic hierarchy process," International Journal of Management and Decision Making, Inderscience Enterprises Ltd, vol. 9(1), pages 75-98.
    9. Pan, Shenle & Ballot, Eric & Fontane, Frédéric, 2013. "The reduction of greenhouse gas emissions from freight transport by pooling supply chains," International Journal of Production Economics, Elsevier, vol. 143(1), pages 86-94.
    10. Yang, Hai & Huang, Hai-Jun, 2004. "The multi-class, multi-criteria traffic network equilibrium and systems optimum problem," Transportation Research Part B: Methodological, Elsevier, vol. 38(1), pages 1-15, January.
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