Skip to main content
SpringerLink
Log in

Intelligent Collaborative Freight Distribution to Reduce Greenhouse Gas Emissions: A Review

  • Chapter
  • First Online:
Computational Intelligence Methodologies Applied to Sustainable Development Goals

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1036))

  • 230 Accesses

Abstract

Freight distribution suffers from inefficiencies which are responsible for a significant part of greenhouse gas emissions. In addition, they have a negative impact on the performance of companies by reducing profits and increasing costs. Among the measures that can be taken to mitigate these effects are cooperation mechanisms. In this work we review optimization models for horizontal collaborative freight transport that include environmental and economic criteria. Specifically, we consider models for planning delivery routes and for cross-docking.

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

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Agustina, D., Lee, C.K.M., Piplani, R.: A review: mathematical models for cross docking planning. Int. J. Eng. Bus. Manag. 2(2), 47–54 (2010)

    Google Scholar 

  2. Aloui, A., Hamani, N., Derrouiche, R., Delahoche, L.: Systematic literature review on collaborative sustainable transportation: overview, analysis and perspectives. Transp. Res. Interdiscip. Perspect. 9, 100291 (2021)

    Google Scholar 

  3. Ballot, E., Fontane, F.: Reducing transportation CO\(_{2}\) emissions through pooling of supply networks: perspectives from a case study in French retail chains. Prod. Plan. Control 21(6), 640–650 (2010)

    Article  Google Scholar 

  4. Bartholdi, III, J.J., Gue, K.R.: The best shape for a crossdock. Transp. Sci. 38(2), 235–244 (2004)

    Google Scholar 

  5. Bektas, T., Laporte, G.: The pollution-routing problem. Transp. Res. Part B 45(8), 1232–1250 (2011)

    Article  Google Scholar 

  6. Boysen, N., Fliedner, M.: Cross dock scheduling: classification, literature review and research agenda. Omega 38(6), 413–422 (2010)

    Article  Google Scholar 

  7. Corlu, C.G., Faulin, J., Onggo, B.S., Juan, A.A., de la Torre, R.: Simulation, optimization, and machine learning in sustainable transportation systems: models and applications. Sustainability 13(3), 1551 (2021)

    Article  Google Scholar 

  8. Cruijssen, F., Cools, M., Dullaert, W.: Horizontal cooperation in logistics: opportunities and impediments. Transp. Res. Part E 43(2), 129–142 (2007)

    Article  Google Scholar 

  9. Danloup, N., Mirzabeiki, V., Allaoui, H., Goncalves, G., Julien, D., Mena, C.: Reducing transportation greenhouse gas emissions with collaborative distribution: a case study. Manag. Res. Rev. 38(10), 1049–1067 (2015)

    Article  Google Scholar 

  10. Dondo, R., Cerdá, J.: A monolithic approach to vehicle routing and operations scheduling of a cross-dock system with multiple dock doors. Comput. Chem. Eng. 63, 184–205 (2014)

    Article  Google Scholar 

  11. Dondo, R., Mández, C.A., Cerdá, J.: The multi-echelon vehicle routing problem with cross docking in supply chain management. Comput. Chem. Eng. 35(12), 3002–3024 (2011)

    Article  Google Scholar 

  12. Enderer, F., Contardo, C., Contreras, I.: Integrating dock-door assignment and vehicle routing with cross-docking. Comput. Oper. Res. 88, 30–43 (2017)

    Article  MathSciNet  Google Scholar 

  13. Gansterer, M., Hartl, R.F.: Collaborative vehicle routing: a survey. Eur. J. Oper. Res. 268(1), 1–12 (2018)

    Article  MathSciNet  Google Scholar 

  14. Gansterer, M., Hartl, R.F.: Shared resources in collaborative vehicle routing. TOP 28(3), 1–20 (2020)

    Article  MathSciNet  Google Scholar 

  15. González-La Rotta, E.C., Becerra-Fernández, M.: Cross-docking with vehicle routing problem. A state of art review [Plataformas de intercambio con ruteo de vehículos. Una revisión del estado del arte]. DYNA (Colombia) 84(200), 271–280 (2017)

    Google Scholar 

  16. Grangier, P., Gendreau, M., Lehuédé, F., Rousseau, L.-M.: A matheuristic based on large neighborhood search for the vehicle routing problem with cross-docking. Comput. Oper. Res. 84, 116–126 (2017)

    Article  MathSciNet  Google Scholar 

  17. Grangier, P., Gendreau, M., Lehéudé, F., Rousseau, L.-M.: The vehicle routing problem with cross-docking and resource constraints. J. Heurist. 27(1), 31–61 (2021)

    Article  Google Scholar 

  18. Hacardiaux, T., Tancrez, J.S.: Assessing the environmental benefits of horizontal cooperation using a location-inventory model. Cent. Eur. J. Oper. Res. 28(4), 1363–1387 (2020)

    Article  MathSciNet  Google Scholar 

  19. Juan Ángel, J., Serrano-Hernández, A., Faulin, J., Pérez-Bernabeu, E.: Horizontal collaboration in freight transport: concepts, benefits, and environmental challenges. Sort 1(2), 1–22 (2017)

    Google Scholar 

  20. Konstantakopoulos, G.D., Gayialis, S.P., Kechagias, E.P., Papadopoulos, G.A., Tatsiopoulos, I.P.: An algorithmic approach for sustainable and collaborative logistics: a case study in Greece. Int. J. Inf. Manage. Data Insights 1(1), 1000010 (2021)

    Google Scholar 

  21. Lee, Y.H., Jung, J.W., Lee, K.M.: Vehicle routing scheduling for cross-docking in the supply chain. Comput. Ind. Eng. 51(2), 247–256 (2006)

    Article  Google Scholar 

  22. Liao, C.-J., Lin, Y., Shih, S.C.: Vehicle routing with cross-docking in the supply chain. Expert Syst. Appl. 37(10), 6868–6873 (2010)

    Article  Google Scholar 

  23. Maknoon, Y., Laporte, G.: Vehicle routing with cross-dock selection. Comput. Oper. Res. 77, 254–266 (2017)

    Article  MathSciNet  Google Scholar 

  24. Mason, R., Lalwani, C., Boughton, R.: Combining vertical and horizontal collaboration for transport optimization. Supply Chain Manag. 12(3), 187–199 (2007)

    Article  Google Scholar 

  25. Mavi, R.K., Goh, M., Mavi, N.K., Jie, F., Brown, K., Biermann, S., Khanfar, A.A.: Cross-docking: a systematic literature review. Sustainability (Switzerland) 12(11) (2020)

    Google Scholar 

  26. Montoya-Torres, J.R., Muñoz-Villamizar A., Vega-Mejía, C.A.: On the impact of collaborative strategies for goods delivery in city logistics. Prod. Plan. Control 27(6), 443–455 (2016)

    Google Scholar 

  27. Morais, V.W.C., Mateus, G.R., Noronha, T.F.: Iterated local search heuristics for the vehicle routing problem with cross-docking. Expert Syst. Appl. 41(16), 7495–7506 (2014)

    Article  Google Scholar 

  28. Mousavi, S.M., Vahdani, B., Tavakkoli-Moghaddam, R., Hashemi, H.: Location of cross-docking centers and vehicle routing scheduling under uncertainty: a fuzzy possibilistic-stochastic programming model. Appl. Math. Model. 38(7–8), 2249–2264 (2014)

    Article  MathSciNet  Google Scholar 

  29. Muñoz-Villamizar, A., Quintero-Araujo, C.L., Montoya-Torres, J.R., Faulin, J.: Short- and mid-term evaluation of the use of electric vehicles in urban freight transport collaborative networks: a case study. Int. J. Logist. Res. Appl. 22(3), 229–252 (2019)

    Google Scholar 

  30. Nataraj, S., Ferone, D., Quintero-Araujo, C., Festa, P., Juan, A.A.: Consolidation centers in city logistics: a cooperative approach based on the location routing problem. Int. J. Ind. Eng. Comput. 10(3), 393–404 (2019)

    Google Scholar 

  31. Nikolopoulou, A.I., Repoussis, P.P., Tarantilis, C.D., Zachariadis, E.E.: Adaptive memory programming for the many-to-many vehicle routing problem with cross-docking. Oper. Res. 19(1) (2019)

    Google Scholar 

  32. Pan, S., Trentesaux, D., Ballot, E., Huang, G.Q.: Horizontal collaborative transport: survey of solutions and practical implementation issues. Int. J. Prod. Res. 57(15–16), 5340–5361 (2019)

    Article  Google Scholar 

  33. Peetijade, C., Bangviwat, A.: Empty trucks run reduction in Bangkok area towards sustainable transportation. Int. J. Trade Econ. Finance 3(2), 91–95 (2012)

    Article  Google Scholar 

  34. Pradenas, L., Oportus, B., Parada, V.: Mitigation of greenhouse gas emissions in vehicle routing problems with backhauling. Expert Syst. Appl. 40(8), 2985–2991 (2013)

    Article  Google Scholar 

  35. Quintero-Araujo, C.L., Gruler, A., Juan, A.A., De Armas, J., Ramalhinho, H.: Using simheuristics to promote horizontal collaboration in stochastic city logistics. Prog. Artif. Intell. 275–284 (2017)

    Google Scholar 

  36. Quintero-Araujo, C.L., Gruler, A., Juan, A.A., Faulin, J.: Using horizontal cooperation concepts in integrated routing and facility-location decisions. Int. Trans. Oper. Res. 26(2), 551–576 (2019)

    Article  MathSciNet  Google Scholar 

  37. Rahbari, A., Nasiri, M.M., Werner, F., Musavi, M., Jolai, F.: The vehicle routing and scheduling problem with cross-docking for perishable products under uncertainty: two robust bi-objective models. Appl. Math. Model. 70, 605–625 (2019)

    Article  MathSciNet  Google Scholar 

  38. Romero, C., Rehman, T.: Multiple Criteria Analysis for Agricultural Decisions. Springer (2013)

    Google Scholar 

  39. Sanchez, M., Pradenas, L., Deschamps, J.C., Parada, V.: Reducing the carbon footprint in a vehicle routing problem by pooling resources from different companies. Netnomics 17(1), 29–45 (2016)

    Article  Google Scholar 

  40. Santos, F.A., Mateus, G.R., Da Cunha, A.S.: The pickup and delivery problem with cross-docking. Comput. Oper. Res. 40(4), 1085–1093 (2013)

    Article  MathSciNet  Google Scholar 

  41. Soysal, M., Bloemhof-Ruwaard, J.M., Haijema, R., van der Vorst, J.G.: Modeling a green inventory routing problem for perishable products with horizontal collaboration. Comput. Oper. Res. 89, 168–182 (2018)

    Article  MathSciNet  Google Scholar 

  42. Stellingwerf, H.M., Laporte, G., Cruijssen, F.C.A.M., Kanellopoulos, A., Bloemhof, J.M.: Quantifying the environmental and economic benefits of cooperation: a case study in temperature-controlled food logistics. Transp. Res. Part D 65, 178–193 (2018)

    Article  Google Scholar 

  43. Stellingwerf, H.M., Kanellopoulos, A., Cruijssen, F.C.A.M., Bloemhof, J.M.: Fair gain allocation in eco-efficient vendor-managed inventory cooperation. J. Clean. Prod. 231(10), 746–755 (2019)

    Article  Google Scholar 

  44. Vahdani, B., Reza, T.-M., Zandieh, M., Razmi, J.: Vehicle routing scheduling using an enhanced hybrid optimization approach. J. Intell. Manuf. 23(3), 759–774 (2012)

    Article  Google Scholar 

  45. Van Belle, J., Valckenaers, P., Cattrysse, D.: Cross-docking: state of the art. Omega 40(6), 827–846 (2012)

    Article  Google Scholar 

  46. Wen, M., Larsen, J., Clausen, J., Cordeau, J.-F., Laporte, G.: Vehicle routing with cross-docking. J. Oper. Res. Soc. 60(12), 1708–1718 (2009)

    Article  Google Scholar 

  47. World Resources Institute, World Business Council for Sustainable Development: The Greenhouse Gas Protocol. A Corporate Accounting and Reporting Standard. World Business Council for Sustainable Development, Geneva; World Resources Institute, Washington, DC (2008)

    Google Scholar 

  48. Yu, V.F., Jewpanya, P., Redi, A.A.N.P.: Open vehicle routing problem with cross-docking. Comput. Ind. Eng. 94, 6–17 (2016)

    Article  Google Scholar 

Download references

Acknowledgements

This work has been partially funded by the Spanish Ministry of Science and Innovation (project PID2019-104410RB-I00).

Author information

Authors and Affiliations

  1. Universidad de La Laguna, San Cristóbal de La Laguna, Spain

    Christopher Expósito-Izquierdo, Belén Melián-Batista, José A. Moreno-Pérez & J. Marcos Moreno-Vega

  2. Kaizten Analytics, San Cristóbal de La Laguna, Spain

    Airam Expósito-Márquez

Authors
  1. Christopher Expósito-Izquierdo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Airam Expósito-Márquez
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Belén Melián-Batista
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. José A. Moreno-Pérez
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. J. Marcos Moreno-Vega
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J. Marcos Moreno-Vega .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain

    José Luis Verdegay

  2. Department of Engineering of Systems, University of La Laguna, San Cristóbal de La Laguna, Spain

    Julio Brito

  3. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain

    Carlos Cruz

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Expósito-Izquierdo, C., Expósito-Márquez, A., Melián-Batista, B., Moreno-Pérez, J.A., Moreno-Vega, J.M. (2022). Intelligent Collaborative Freight Distribution to Reduce Greenhouse Gas Emissions: A Review. In: Verdegay, J.L., Brito, J., Cruz, C. (eds) Computational Intelligence Methodologies Applied to Sustainable Development Goals. Studies in Computational Intelligence, vol 1036. Springer, Cham. https://doi.org/10.1007/978-3-030-97344-5_9

Download citation

Publish with us

Policies and ethics

Search

Navigation