Skip to main content

Advertisement

SpringerLink
Log in

A biofuel supply chain design considering sustainability, uncertainty, and international suppliers and markets

  • Original Article
  • Published:
Biomass Conversion and Biorefinery Aims and scope Submit manuscript

Abstract

Climate change, global warming, and the negative consequences of fossil fuels on human life and the environment have prompted governments to seek a long-term replacement for fossil fuels, such as biofuel. According to a few considerations of sustainable supplier selection in the area of constructing biofuel supply chains, import and export activities, financial decisions, and all aspects of sustainability at the same time, this research creates a novel multi-objective model for designing a biofuel supply chain by incorporating financial decisions, sustainability, international suppliers and markets. Supplier selection criteria are weighted using the fuzzy best-worst method, and suppliers are ranked using fuzzy TOPSIS. A possibilistic programming approach based on the Me fuzzy measure is utilized to deal with parameter uncertainties. A fuzzy programming approach is implemented to solve the model. To demonstrate the applicability of the suggested model, an actual case study in Iran is used. The numerical results show that biofuel production and transportation operations account for the bulk of overall costs. Greenhouse gas emissions and the amount of water required contribute significantly to the environmental goal. When compared to deterministic models, profit and social objectives are lower in uncertain models, while order allocation and environmental objectives are higher, but the system will hedge against the high level of uncertainty. In conclusion, the suggested model has a notable impact on improving sustainable facets and can be implemented by governments and legislators.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Ikram M, Zhou P, Shah SAAAA, Liu GQQ (2019) Do environmental management systems help improve corporate sustainable development? Evidence from manufacturing companies in Pakistan. J Clean Prod 226:628–641

    Google Scholar 

  2. Lin CY, Alam SS, Ho YH, al Shaikh ME, Sultan P (2020) Adoption of green supply chain management among SMEs in Malaysia. Sustainability. 12:6454

    Google Scholar 

  3. Jum’a L, Ikram M, Alkalha Z, Alaraj M (2022) Factors affecting managers’ intention to adopt green supply chain management practices: evidence from manufacturing firms in Jordan. Environ Sci Pollut Res 29(4): 5605-5621

  4. Asadi E, Habibi F, Nickel S, Sahebi H (2018) A bi-objective stochastic location-inventory-routing model for microalgae-based biofuel supply chain. Appl Energy 228:2235–2261

    Google Scholar 

  5. Yang B, Wang Y, Qian PY (2016) Sensitivity and correlation of hypervariable regions in 16S rRNA genes in phylogenetic analysis. BMC Bioinforma 17:1–8

    Google Scholar 

  6. U.S. Energy Information Administration (EIA) (2009) World proved reserves of oil and natural gas, most recent estimates. https://www.eia.gov/

  7. Ghelichi Z, Saidi Mehrabad M, Pishvaee MS (2018) A stochastic programming approach toward optimal design and planning of an integrated green biodiesel supply chain network under uncertainty: a case study. Energ. 156:661–687

    Google Scholar 

  8. Shalaby EA (2013) Biofuel: sources, extraction and determination, Liquid, gaseous and solid biofuels-conversion techniques Croatia. InTech. 20:451–478

    Google Scholar 

  9. Brennan L, Owende P (2010) Biofuels from microalga—a review of technologies for production, processing, and extractions of biofuels and co-products. Renew Sust Energ Rev 14(2):557–577

    Google Scholar 

  10. IEA (2012) CO2 Emissions from Fuel Combustion. International Energy Agency Statistics, Paris

    Google Scholar 

  11. Baghizadeh K, Zimon D, Jum’a L (2021) Modeling and optimization sustainable forest supply chain considering discount in transportation system and supplier selection under uncertainty. Forests. 12:964

    Google Scholar 

  12. Ghafoor A, ur Rehman T, Munir A, Ahmad M, Iqbal M (2016) Current status and overview of renewable energy potential in Pakistan for continuous energy sustainability. Renew Sust Energ Rev 60:1332–1342

    Google Scholar 

  13. Forest Products Association of Canada (FPAC) (2011) The new face of the Canadian forest industry. https://www.fpac.ca/reports/the-new-face-of-the-canadian-forest-industry

  14. Natural Resources Canada (NRC) (2015) Forest bio economy, bioenergy and bio products. https://www.nrcan.gc.ca/our-natural-resources/forests/industry-and-trade/forest-bioeconomy-bioenergy-bioproducts/13315

  15. Gitinavard H, Shirazi MA, Zarandi MHF (2020) Sustainable feedstocks selection and renewable products allocation: A new hybrid adaptive utility-based consensus model. J Environ Manag 264:110428

    Google Scholar 

  16. Landis DA, Gardiner MM, van der Werf W, Swinton SM (2008) Increasing corn for biofuel production reduces biocontrol services in agricultural landscapes. Proc Natl Acad Sci 105(51):20552–20557

    Google Scholar 

  17. Banaeian N, Zangeneh M (2011) Study on energy efficiency in corn production of Iran. Energy. 36(8):5394–5402

    Google Scholar 

  18. Krajewski LJ, Ritzman LP (2002) Operations management: strategy and analysis, 120th edn. Prentice Hall, Upper Saddle River

    Google Scholar 

  19. Gupta S, Soni U, Kumar G (2019) Green supplier selection using multi-criterion decision making under fuzzy environment: a case study in automotive industry. Comput Ind Eng 136:663–680

    Google Scholar 

  20. Nguyen DH, Chen H (2018) Supplier selection and operation planning in biomass supply chains with supply uncertainty. Comput Chem Eng 118:103–117

    Google Scholar 

  21. Galankashi MR, Chegeni A, Soleimanynanadegany A, Memari A, Anjomshoae A, Helmi SA, Dargi A (2015) Prioritizing green supplier selection criteria using fuzzy analytical network process. Proc Cirp 26:689–694

    Google Scholar 

  22. Helpman E, Krugman PR (1985) Market structure and foreign trade: increasing returns, imperfect competition, and the international economy. MIT press, Cambridge

    Google Scholar 

  23. Aladejare SA, Saidi A (2014) Determinants of non-oil export and economic growth in Nigeria: An application of the bound test approach. J Adv Dev Econ 3(1):68–81

    Google Scholar 

  24. Mosikari TJ, Eita JH (2020) Modelling asymmetric relationship between exports and growth in a developing economy: evidence from Namibia. S Afr J Econ Manag Sci 23(1):1–10

    Google Scholar 

  25. Balassa B (1978) Exports and economic growth: further evidence. J Dev Econ 5(2):181–189

    Google Scholar 

  26. Bhagwati JN, Srinivasan TN (1979) On inferring resource-allocational implications from DRC calculations in trade-distorted small open economies. Indian Econ Rev 14(1):1–16

    Google Scholar 

  27. Krueger AO (1980) Trade policy as an input to development. Am Econ Rev 70(2):288–292

    Google Scholar 

  28. Semaa H, Hou MA, Fadili Z, Farhaoui Y, Malhouni B (2020) Design of an efficient strategy for optimization of payment induced by a rational supply chain process: a prerequisite for maintaining a satisfactory level of working capital. Proc Comp Sci 170:881–886

    Google Scholar 

  29. Jum’a L, Zimon D, Ikram M, Madzík P (2022) Towards a sustainability paradigm; the nexus between lean green practices, sustainability-oriented innovation and triple bottom line. Int J Prod Econ 245:108393

    Google Scholar 

  30. Afkhami P, Zarrinpoor N (2021) Optimization design of a supply chain for Jatropha-based biofuel from a sustainable development perspective considering international resources and demand: a case study. Ind Eng Chem Res 60:6188–6207

    Google Scholar 

  31. Babazadeh R, Ghaderi H, Pishvaee MS (2019) A benders-local branching algorithm for second-generation biodiesel supply chain network design under epistemic uncertainty. Comput Chem Eng 124:364–380

    Google Scholar 

  32. Zamboni A, Bezzo F, Shah N (2009) Spatially explicit static model for the strategic design of future bioethanol production systems. 2. Multi-objective environmental optimization. Energy Fuel 23(10):5134–5143

    Google Scholar 

  33. Corsano G, Vecchietti AR, Montagna JM (2011) Optimal design for sustainable bioethanol supply chain considering detailed plant performance model. Comput Chem Eng 35:1384–1398

    Google Scholar 

  34. An H, Wilhelm WE, Searcy SW (2011) A mathematical model to design a lignocellulosic biofuel supply chain system with a case study based on a region in Central Texas. Bioresour Technol 102(17):7860–7870

    Google Scholar 

  35. Azadeh A, Arani HV, Dashti H (2014) A stochastic programming approach towards optimization of biofuel supply chain. Energy. 76:513–525

    Google Scholar 

  36. Cambero C, Sowlati T (2016) Incorporating social benefits in multi-objective optimization of forest-based bioenergy and biofuel supply chains. Appl Energy 178:721–735

    Google Scholar 

  37. Hombach LE, Cambero C, Sowlati T, Walther G (2016) Optimal design of supply chains for second generation biofuels incorporating European biofuel regulations. J Clean Prod 133:565–575

    Google Scholar 

  38. Ren J, An D, Liang H, Dong L, Gao Z, Geng Y, Zhu Q, Song S, Zhao W (2016) Life cycle energy and CO2 emission optimization for biofuel supply chain planning under uncertainties. Energy. 103:151–166

    Google Scholar 

  39. Babazadeh R, Razmi J, Pishvaee MS, Rabbani M (2017) A sustainable second-generation biodiesel supply chain network design problem under risk. Omega. 66:258–277

    Google Scholar 

  40. Bairamzadeh S, Saidi-Mehrabad M, Pishvaee MS (2018) Modelling different types of uncertainty in biofuel supply network design and planning: A robust optimization approach. Renew Energy 116:500–517

    Google Scholar 

  41. Fattahi M, Govindan K (2018) A multi-stage stochastic program for the sustainable design of biofuel supply chain networks under biomass supply uncertainty and disruption risk: a real-life case study. Transp Res Part E: Logist Transp Rev 118:534–567

    Google Scholar 

  42. Kesharwani R, Sun Z, Dagli C, Xiong H (2019) Moving second generation biofuel manufacturing forward: Investigating economic viability and environmental sustainability considering two strategies for supply chain restructuring. Appl Energy 242:1467–1496

    Google Scholar 

  43. Ghosh T, Bakshi BR (2019) Designing biofuel supply chains while mitigating harmful algal blooms with treatment wetlands. Comput Chem Eng 126:113–127

    Google Scholar 

  44. Nugroho YK, Zhu L (2019) Platforms planning and process optimization for biofuels supply chain. Renew Energy 140:563–579

    Google Scholar 

  45. Zahraee SM, Golroudbary SR, Shiwakoti N, Kraslawski A, Stasinopoulos P (2019) An investigation of the environmental sustainability of palm biomass supply chains via dynamic simulation modeling: a case of Malaysia. J Clean Prod 237:117740

    Google Scholar 

  46. Esmaeili SAH, Szmerekovsky J, Sobhani A, Dybing A, Peterson TO (2020) Sustainable biomass supply chain network design with biomass switching incentives for first-generation bioethanol producers. Energy Policy 138:111222

    Google Scholar 

  47. Zahraee SM, Shiwakoti N, Stasinopoulos P (2020) Biomass supply chain environmental and socio-economic analysis: 40-Years comprehensive review of methods, decision issues, sustainability challenges, and the way forward. Biomass Bioenergy 142:105777

    Google Scholar 

  48. Mahjoub N, Sahebi H, Mazdeh M, Teymouri A (2020) Optimal design of the second and third generation biofuel supply network by a multi-objective model. J Clean Prod 256:120355

    Google Scholar 

  49. Kang S, Heo S, Realff MJ, Lee JH (2020) Three-stage design of high-resolution microalgae-based biofuel supply chain using geographic information system. Appl Energy 265:114773

    Google Scholar 

  50. Gilani H, Sahebi (2021) A multi-objective robust optimization model to design sustainable sugarcane-to-biofuel supply network: the case of study, Biomass Conver Biorefinery 11(6): 2521-2542

  51. Zarrinpoor N, Khani A (2021) Designing a sustainable biofuel supply chain by considering carbon policies: a case study in Iran. Energy, Sustain Soc 11(38)

  52. Mohammadi F, Sahebi H, Abdali H (2021) Biofuel production from sewage sludge network under disruption condition: studying energy-water nexus. Biomass Conver Biorefinery 1-11

  53. Moretti L, Milani M, Lozza GG, Manzolini G (2021) A detailed MILP formulation for the optimal design of advanced biofuel supply chains. Renew Energy 171:159–175

    Google Scholar 

  54. Geng N, Sun Y (2021) Multiobjective Optimization of Sustainable WCO for Biodiesel Supply Chain Network Design. Discret Dyn Nat Soc

  55. Memari Y, Memari A, Ebrahimnejad S, Ahmad R (2021) A mathematical model for optimizing a biofuel supply chain with outsourcing decisions under the carbon trading mechanism. Biomass Conver Biorefinery 1-24

  56. Afkhami P, Zarrinpoor N (2022) The energy-water-food-waste-land nexus in a GIS-based biofuel supply chain design: A case study in Fars province, Iran. J Clean Prod 340:130690

    Google Scholar 

  57. O’Neill EG, Martinez-Feria RA, Basso B, Maravelias CT (2022) Integrated spatially explicit landscape and cellulosic biofuel supply chain optimization under biomass yield uncertainty. Comput Chem Eng 160:107724

    Google Scholar 

  58. Yazdanparast R, Jolai F, Pishvaee MS, Keramati A (2022) A resilient drop-in biofuel supply chain integrated with existing petroleum infrastructure: toward more sustainable transport fuel solutions. Renew Energy 184:799–819

    Google Scholar 

  59. Hashemi SH, Karimi A, Tavana M (2015) An integrated green supplier selection approach with analytic network process and improved Grey relational analysis. Int J Prod Econ 159:178–191

    Google Scholar 

  60. Kannan D (2018) Role of multiple stakeholders and the critical success factor theory for the sustainable supplier selection process. Int J Prod Econ 195:391–418

    Google Scholar 

  61. Hsu CW, Kuo TC, Chen SH, Hu AH (2013) Using DEMATEL to develop a carbon management model of supplier selection in green supply chain management. J Clean Prod 56:164–172

    Google Scholar 

  62. Sarkis J, Dhavale DG (2015) Supplier selection for sustainable operations: a triple-bottom-line approach using a Bayesian framework. Int J Prod Econ 166:177–191

    Google Scholar 

  63. Sawik B (2016, 2016) Multi-criteria mathematical programming approaches for assignment of services in hospital. ICIL:239À246

  64. Dos Santos BM, Godoy LP, Campos LM (2019) Performance evaluation of green suppliers using entropy-TOPSIS-F. J Clean Prod 207:498–509

    Google Scholar 

  65. Chan FT, Kumar N (2007) Global supplier development considering risk factors using fuzzy extended AHP-based approach. Omega 35(4):417–431

    Google Scholar 

  66. Büyüközkan G, Çifçi G (2011) A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information. Comput Ind 62(2):164–174

    Google Scholar 

  67. Yu Q, Hou F (2016) An approach for green supplier selection in the automobile manufacturing industry. Kybernetes.

  68. Rajesh R, Ravi V (2015) Supplier selection in resilient supply chains: a grey relational analysis approach. J Clean Prod 86:343–359

    Google Scholar 

  69. Punniyamoorthy M, Mathiyalagan P, Parthiban P (2011) A strategic model using structural equation modeling and fuzzy logic in supplier selection. Expert Syst Appl 38(1):458–474

    Google Scholar 

  70. Hsu TH, Hung LC, Tang JW (2012) The multiple criteria and sub-criteria for electronic service quality evaluation: an interdependence perspective. Online Inf Rev

  71. Chiou CY, Hsu CW, Hwang WY (2008) December. Comparative investigation on green supplier selection of the American, Japanese and Taiwanese electronics industry in China. In: 2008 IEEE International Conference on Industrial Engineering and Engineering Management. IEEE, pp 1909–1914. https://doi.org/10.1109/IEEM.2008.4738204

  72. Rezaei J, Ortt R (2013) Multi-criteria supplier segmentation using a fuzzy preference relations based AHP. Eur J Oper Res 225(1):75–84

    MATH  Google Scholar 

  73. Akman G, Özcan B, Hatipoğlu T (2015) Fuzzy multi criteria decision making approach to innovative strategies based on Miles and Snow typology. J Intell Manuf 26(3):609–628

    Google Scholar 

  74. Alaoui ME, Yassini KE, Ben-azza H (2019) Type 2 fuzzy TOPSIS for agriculture MCDM problems. Int J Sustain Agric Manag Inform 5(2-3):112–130

    Google Scholar 

  75. Arif M, Bendi D, Toma-Sabbagh T, Sutrisna M (2012) Construction waste management in India: an exploratory study. Constr Innov

  76. Pappu A, Saxena M, Asolekar SR (2007) Solid wastes generation in India and their recycling potential in building materials. Build Environ 42(6):2311–2320

    Google Scholar 

  77. Ramaswamy KP, Kalidindi, SN (2009) Waste in Indian building construction projects. In: Proceedings of the 17th Annual Conference of the IGLC. Taipei. https://iglcstorage.blob.core.windows.net/papers/attachment-5e8b0d2e-90e6-4d1f-94fd-a518ab87a9cb.pdf

  78. Joseph P, Tretsiakova-McNally S (2010) Sustainable non-metallic building materials. Sustainability 2(2):400–427

    Google Scholar 

  79. Spiegel R, Meadows D (2010) Green building materials: a guide to product selection and specification. John Wiley & Sons, Hoboken

    Google Scholar 

  80. Mathiyazhagan K, Gnanavelbabu A, Prabhuraj BL (2018) A sustainable assessment model for material selection in construction industries perspective using hybrid MCDM approaches. J Adv Manag Res 10:31–44

    Google Scholar 

  81. Tavana M, Arteaga FJ, Mohammadi S, Alimohammadi M (2017) A fuzzy multi-criteria spatial decision support system for solar farm location planning. Energy Strategy Rev 18:93–105

    Google Scholar 

  82. Blome C, Hollos D, Paulraj A (2014) Green procurement and green supplier development: antecedents and effects on supplier performance. Int J Prod Res 52(1):32–49

    Google Scholar 

  83. Zhou X, Xu Z (2018) An integrated sustainable supplier selection approach based on hybrid information aggregation. Sustainability. 10(7):2543

    Google Scholar 

  84. Rezaei J (2015) Best-worst multi-criteria decision-making method. Omega 53:49–57

    Google Scholar 

  85. Guo S, Zhao H (2017) Fuzzy best-worst multi-criteria decision-making method and its applications. Knowl-Based Syst 121:23–31

    Google Scholar 

  86. Chen CT (2000) Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst 114(1):1–9

    MATH  Google Scholar 

  87. Hwang CL, Yoon K (1981) Methods for multiple attribute decision making. In: Multiple attribute decision making. Springer, Berlin, pp 58–191

    Google Scholar 

  88. 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

    Google Scholar 

  89. Goli A, Zare HK, Tavakkoli Moghaddam R, Sadegheih A (2020) Multiobjective fuzzy mathematical model for a financially constrained closed-loop supply chain with labor employment. Comput Intell 36(1):4–34

    MathSciNet  Google Scholar 

  90. Global Reporting Initiative (GRI) (2020) Consolidated set of GRI sustainability reporting standards. Available at: https://www.globalreporting.org/search/?query=Consolidated+set+of+GRI. Accessed 8 Oct 2021

  91. Zhalechian M, Tavakkoli-Moghaddam R, Rahimi Y, Jolai F (2017) An interactive possibilistic programming approach for a multi-objective hub location problem: Economic and environmental design. Appl Soft Comput 52:699–713

    Google Scholar 

  92. Liu B (2009) Fuzzy programming. In: Theory and practice of uncertain programming. Springer, Berlin, pp 57–82

    Google Scholar 

  93. Xu J, Zhou X (2013) Approximation based fuzzy multi-objective models with expected objectives and chance constraints: application to earth-rock work allocation. Inf Sci 238:75–95

    MathSciNet  MATH  Google Scholar 

  94. Pishvaee MS, Razmi J (2012) Environmental supply chain network design using multi-objective fuzzy mathematical programming. Appl Math Model 36(8):3433–3446

    MathSciNet  MATH  Google Scholar 

  95. Torabi SA, Hassini E (2008) An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy Sets Syst 159(2):193–214

    MathSciNet  MATH  Google Scholar 

  96. Mohseni S, Pishvaee M (2019) Supply chain management models for the development of green fuel production from microalgae in Iran. J Environ Sci Technol 21(2):189–210

    Google Scholar 

  97. Ghelichi Z, Saidi-mehrabad M, Pishvaee MS (2018) A stochastic programming approach towardoptimal design and planning of an integrated green biodiesel supply chain network under uncertainty : a case study. Energy. 156:661–687

    Google Scholar 

  98. Meyer R, Campanella S, Corsano G, Montagna JM (2019) Optimal design of a forest supply chain in Argentina considering economic and social aspects. J Clean Prod 231:224–239

    Google Scholar 

  99. Rahimi M, Ghezavati V, Asadi F (2019) A stochastic risk-averse sustainable supply chain network design problem with quantity discount considering multiple sources of uncertainty. Comput Ind Eng 130:430–449

    Google Scholar 

  100. Pérez ATE, Rincón PCN, Camargo M, Marchant MDA (2019) Multiobjective optimization for the design of phase III biorefinery sustainable supply chain. J Clean Prod 223:189–213

    Google Scholar 

  101. Zarrinpoor N, Pishvaee MS (2021) Designing a municipal solid waste management system under disruptions using an enhanced L-shaped method. J Clean Prod 299:126672

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Shiraz University of Technology, Shiraz, Iran

    Naeme Zarrinpoor & Aida Khani

Authors
  1. Naeme Zarrinpoor
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aida Khani
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All persons who meet authorship criteria are listed as authors, and all authors certify that they have participated sufficiently in the work to take public responsibility for the content, including participation in the concept, design, analysis, and writing of the manuscript.

Corresponding author

Correspondence to Naeme Zarrinpoor.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zarrinpoor, N., Khani, A. A biofuel supply chain design considering sustainability, uncertainty, and international suppliers and markets. Biomass Conv. Bioref. 13, 14127–14153 (2023). https://doi.org/10.1007/s13399-022-02804-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13399-022-02804-7

Keywords

Search

Navigation