Skip to main content

Advertisement

SpringerLink
Log in

A location-inventory-routing model for green supply chains with low-carbon emissions under uncertainty

  • Research Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

The location-inventory-routing modeling is an integrated and comprehensive approach to the interconnected location planning, inventory management, and vehicle routing problems in supply chain management. Supplier selection and order allocation are critical operational and strategic decisions in green supply chains. Green supply chain management is an environmental approach to sourcing and production that considers sustainability in every supply chain stage. In this study, a novel bi-objective mixed-integer linear programming model is formulated to solve the location-inventory-routing problems in green supply chains with low-carbon emissions under uncertainty. The proposed model is used for supplier selection and order allocation by considering the location priorities, heterogeneous vehicle routing, storage needs, uncertain demand, and backorder shortage. The formulated bi-objective model is solved with a weighted fuzzy multi-objective solution approach coupled with a novel intelligent simulation algorithm to ensure the feasibility of the solution space. We generate and solve different-sized problems to demonstrate the applicability and efficacy of the proposed model.

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

Similar content being viewed by others

Data Availability

Not applicable

References

  • Amin SH, Zhang G, Akhtar P (2017) Effects of uncertainty on a tire closed-loop supply chain network. Expert Syst Appl 73:82–91

    Google Scholar 

  • 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 

  • Biuki M, Kazemi A, Alinezhad A (2020) An integrated location-routing-inventory model for sustainable design of a perishable products supply chain network. J Clean Prod 260:120842

    Google Scholar 

  • Fathollahi-Fard AM, Hajiaghaei-Keshteli M, Mirjalili S (2018) Multi-objective stochastic closed-loop supply chain network design with social considerations. Appl Soft Comput 71:505–525

    Google Scholar 

  • Fathollahi-Fard AM, Ahmadi A, Mirzapour Al-e-Hashem SMJ (2020) Sustainable closed-loop supply chain network for an integrated water supply and wastewater collection system under uncertainty. J Environ Manag 275:111277

    Google Scholar 

  • Feng Y, Zhang Z, Tian G, Fathollahi-Fard AM, Hao N, Li Z, Wang W, Tan J (2019) A novel hybrid fuzzy grey TOPSIS method: supplier evaluation of a collaborative manufacturing enterprise. Appl Sci 9(18):3770

    Google Scholar 

  • Gholipour S, Ashoftehfard A, Mina H (2020) Green supply chain network design considering inventory-location-routing problem: a fuzzy solution approach. Int J Logist Syst Manag 35(4):436–452

    Google Scholar 

  • Goodarzian F, Hosseini-Nasab H, Muñuzuri J, Fakhrzad MB (2020) A multi-objective pharmaceutical supply chain network based on a robust fuzzy model: a comparison of meta-heuristics. Appl Soft Comput 92:106331

    Google Scholar 

  • Govindan K, Jafarian A, Nourbakhsh V (2019) Designing a sustainable supply chain network integrated with vehicle routing: a comparison of hybrid swarm intelligence metaheuristics. Comput Oper Res 110:220–235

    Google Scholar 

  • Govindan K, Mina H, Esmaeili A, Gholami-Zanjani SM (2020) An integrated hybrid approach for circular supplier selection and closed loop supply chain network design under uncertainty. J Clean Prod 242:118317

    Google Scholar 

  • Hajiaghaei-Keshteli M, Fard AMF (2019) Sustainable closed-loop supply chain network design with discount supposition. Neural Comput & Applic 31(9):5343–5377. https://doi.org/10.1007/s00521-018-3369-5

    Article  Google Scholar 

  • Hajiaghaei-Keshteli M, Abdallah KS, Fathollahi-Fard AM (2018) A collaborative stochastic closed-loop supply chain network design for tire industry. Int J Eng 31(10):1715–1722

    Google Scholar 

  • Hiassat A, Diabat A, Rahwan I (2017) A genetic algorithm approach for location-inventory-routing problem with perishable products. J Manuf Syst 42:93–103

    Google Scholar 

  • Hsiao YH, Chen MC, Chin CL (2017) Distribution planning for perishable foods in cold chains with quality concerns: formulation and solution procedure. Trends Food Sci Technol 61:80–93

    CAS  Google Scholar 

  • Iqbal MW, Kang Y, Jeon HW (2020) Zero waste strategy for green supply chain management with minimization of energy consumption. J Clean Prod 245:118827

    Google Scholar 

  • Kannan D, Mina H, Nosrati-Abarghooee S, Khosrojerdi G (2020) Sustainable circular supplier selection: a novel hybrid approach. Sci Total Environ 722:137936–137936

    CAS  Google Scholar 

  • Karampour MM, Hajiaghaei-Keshteli M, Fathollahi-Fard AM, Tian G (2020) Metaheuristics for a bi-objective green vendor managed inventory problem in a two-echelon supply chain network. Sci Iran. https://doi.org/10.24200/sci.2020.53420.3228

  • Kargar S, Pourmehdi M, Paydar MM (2020) Reverse logistics network design for medical waste management in the epidemic outbreak of the novel coronavirus (COVID-19). Sci Total Environ 746:141183

    CAS  Google Scholar 

  • Kaya O, Ozkok D (2020) A blood bank network design problem with integrated facility location, inventory and routing decisions. Netw Spat Econ 20(3):757–783

    Google Scholar 

  • 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 

  • Mardan E, Govindan K, Mina H, Gholami-Zanjani SM (2019) An accelerated benders decomposition algorithm for a bi-objective green closed loop supply chain network design problem. J Clean Prod 235:1499–1514

    Google Scholar 

  • Mohammed A, Harris I, Soroka A, Nujoom R (2019) A hybrid MCDM-fuzzy multi-objective programming approach for a G-Resilient supply chain network design. Comput Ind Eng 127:297–312

    Google Scholar 

  • Nasr AK, Tavana M, Alavi B, Mina H (2021) A novel fuzzy multi-objective circular supplier selection and order allocation model for sustainable closed-loop supply chains. J Clean Prod 287:124994

    Google Scholar 

  • Nurjanni KP, Carvalho MS, Costa L (2017) Green supply chain design: a mathematical modeling approach based on a multi-objective optimization model. Int J Prod Econ 183:421–432

    Google Scholar 

  • Qazvini ZE, Amalnick MS, Mina H (2016) A green multi-depot location routing model with split-delivery and time window. Int J Manag Concepts Philos 9(4):271–282

    Google Scholar 

  • Qazvini ZE, Haji A, Mina H (2019) A fuzzy solution approach for supplier selection and order allocation in green supply chain considering location-routing problem. Sci Iran Trans E Ind Eng, In Press. https://doi.org/10.24200/sci.2019.50829.1885

  • Rabbani M, Heidari R, Farrokhi-Asl H, Rahimi N (2018) Using metaheuristic algorithms to solve a multi-objective industrial hazardous waste location-routing problem considering incompatible waste types. J Clean Prod 170:227–241

    Google Scholar 

  • Rafie-Majd Z, Pasandideh SHR, Naderi B (2018) Modelling and solving the integrated inventory-location-routing problem in a multi-period and multi-perishable product supply chain with uncertainty: Lagrangian relaxation algorithm. Comput Chem Eng 109:9–22

    CAS  Google Scholar 

  • 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 

  • Rastegar M, Tavana M, Meraj A, Mina H (2021) An inventory-location optimization model for equitable influenza vaccine distribution in developing countries during the COVID-19 pandemic. Vaccine 39(3):495–504

    CAS  Google Scholar 

  • Safaeian M, Fathollahi-Fard AM, Tian G, Li Z, Ke H (2019) A multi-objective supplier selection and order allocation through incremental discount in a fuzzy environment. J Intell Fuzzy Syst 37(1):1435–1455

    Google Scholar 

  • Sahebjamnia N, Fathollahi-Fard AM, Hajiaghaei-Keshteli M (2018) Sustainable tire closed-loop supply chain network design: hybrid metaheuristic algorithms for large-scale networks. J Clean Prod 196:273–296

    Google Scholar 

  • Saif-Eddine AS, El-Beheiry MM, El-Kharbotly AK (2019) An improved genetic algorithm for optimizing total supply chain cost in inventory location routing problem. Ain Shams Eng J 10(1):63–76

    Google Scholar 

  • Saragih NI, Bahagia N, Syabri I (2019) A heuristic method for location-inventory-routing problem in a three-echelon supply chain system. Comput Ind Eng 127:875–886

    Google Scholar 

  • Savadkoohi E, Mousazadeh M, Torabi SA (2018) A possibilistic location-inventory model for multi-period perishable pharmaceutical supply chain network design. Chem Eng Res Des 138:490–505

    CAS  Google Scholar 

  • Shaw K, Shankar R, Yadav SS, Thakur LS (2012) Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain. Expert Syst Appl 39(9):8182–8192

    Google Scholar 

  • Tamannaei M, Rasti-Barzoki M (2019) Mathematical programming and solution approaches for minimizing tardiness and transportation costs in the supply chain scheduling problem. Comput Ind Eng 127:643–656

    Google Scholar 

  • Tavana M, Abtahi AR, Di Caprio D, Hashemi R, Yousefi-Zenouz R (2018) An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations. Socio Econ Plan Sci 64:21–37

    Google Scholar 

  • Vahdani B, Veysmoradi D, Noori F, Mansour F (2018) Two-stage multi-objective location-routing-inventory model for humanitarian logistics network design under uncertainty. Int J Dis Risk Reduction 27:290–306

    Google Scholar 

  • Veenstra M, Roodbergen KJ, Coelho LC, Zhu SX (2018) A simultaneous facility location and vehicle routing problem arising in health care logistics in the Netherlands. Eur J Oper Res 268(2):703–715

    Google Scholar 

  • Wu W, Zhou W, Lin Y, Xie Y, Jin W (2021) A hybrid metaheuristic algorithm for location inventory routing problem with time windows and fuel consumption. Expert Syst Appl 166:114034

    Google Scholar 

  • Yavari M, Enjavi H, Geraeli M (2020) Demand management to cope with routes disruptions in location-inventory-routing problem for perishable products. Res Transp Bus Manag 37:100552

    Google Scholar 

  • Yuchi Q, Wang N, He Z, Chen H (2021) Hybrid heuristic for the location-inventory-routing problem in closed-loop supply chain. Int Trans Oper Res 28(3):1265–1295

    Google Scholar 

  • Zandkarimkhani, S., Mina, H., Biuki, M., & Govindan, K. (2020). A chance constrained fuzzy goal programming approach for perishable pharmaceutical supply chain network design. Ann Oper Res 1-28.

  • Zhalechian M, Tavakkoli-Moghaddam R, Zahiri B, Mohammadi M (2016) Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty. Transp Res Part E: Logist Transp Rev 89:182–214

    Google Scholar 

  • Zheng MM, Li W, Liu Y, Liu X (2020) A Lagrangian heuristic algorithm for sustainable supply chain network considering CO2 emission. J Clean Prod 270:122409

    Google Scholar 

Download references

Acknowledgment

M.T. is grateful for the partial support he received from the Czech Science Foundation (GAˇCR19-13946S) for this research.

Author information

Authors and Affiliations

  1. Business Systems and Analytics Department, La Salle University, Philadelphia, PA, 19141, USA

    Madjid Tavana

  2. Business Information Systems Department, Faculty of Business Administration and Economics, University of Paderborn, D-33098, Paderborn, Germany

    Madjid Tavana

  3. Department of Industrial Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran

    Hamid Tohidi, Milad Alimohammadi & Reza Lesansalmasi

Authors
  1. Madjid Tavana
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hamid Tohidi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Milad Alimohammadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Reza Lesansalmasi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.T.: conceptualization; methodology; formal analysis; writing—original draft; writing—review and editing; visualization. H.T.: supervision; investigation; data curation. M.A.: investigation; validation; data curation. R.L.: investigation; data curation; software. H.M.: conceptualization; writing—review and editing; visualization.

Corresponding author

Correspondence to Madjid Tavana.

Ethics declarations

Ethics approval

Not applicable

Consent to participate

Not applicable

Consent for publication

Not applicable

Competing interests

The above authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Declaration of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Responsible Editor: Philippe Garrigues

Publisher’s note

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

Supplementary Information

ESM 1

(DOCX 56 kb)

Appendix

Appendix

Data simulation model

figure a

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tavana, M., Tohidi, H., Alimohammadi, M. et al. A location-inventory-routing model for green supply chains with low-carbon emissions under uncertainty. Environ Sci Pollut Res 28, 50636–50648 (2021). https://doi.org/10.1007/s11356-021-13815-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-021-13815-8

Keywords

Search

Navigation