IDEAS home Printed from https://ideas.repec.org/a/gam/jlogis/v6y2022i2p32-d818994.html
   My bibliography  Save this article

Analysis of Decision Parameters for Route Plans and Their Importance for Sustainability: An Exploratory Study Using the TOPSIS Technique

Author

Listed:
  • Alice Vasconcelos Nobre

    (Production Engineering Course, State University of Pará, Castanhal 68745-000, Brazil)

  • Caio Cézar Rodrigues Oliveira

    (Production Engineering Course, State University of Pará, Castanhal 68745-000, Brazil)

  • Denilson Ricardo de Lucena Nunes

    (Department of Production Engineering, State University of Pará, Castanhal 68745-000, Brazil)

  • André Cristiano Silva Melo

    (Postgraduate Program in Technology, Natural Resources and Sustainability in the Amazon (PPGTEC/CCNT/UEPA), Department of Production Engineering, State University of Pará, Belém 66095-015, Brazil)

  • Gil Eduardo Guimarães

    (Production Engineering Course, Universidade de Cruz Alta, Cruz Alta 98005-972, Brazil)

  • Rosley Anholon

    (Faculty of Mechanical Engineering, University of Campinas, Campinas 13083-860, Brazil)

  • Vitor William Batista Martins

    (Postgraduate Program in Technology, Natural Resources and Sustainability in the Amazon (PPGTEC/CCNT/UEPA), Department of Production Engineering, State University of Pará, Belém 66095-015, Brazil)

Abstract

Background: This study aimed to identify the most widespread performance objectives for the vehicle routing problem, the degree of comparative importance attributed to each of these performance objectives in the opinion of professionals in the logistics area working in Brazil and also relate them to aspects of sustainability considering environmental, economic and social issues. Methods: To this end, a literature review was carried out in the area and a survey was developed with professionals through a structured questionnaire. The collected data were treated using the TOPSIS multi-criteria technique. Results: The results indicate that the performance objectives in route plans “level of service”, “total number of vehicles” and “total distance travelled” are the ones that, in the opinion of the professionals participating in the research, have greater importance in the planning and elaboration of plan routes and that such objectives directly impact the sustainable results of a given organization. Conclusions: The results can serve as a basis for researchers in the area who aim to broaden the debates on this topic and for logistics operations managers who work directly with planning and elaboration of route plans and who aim to make their operations more sustainable. Therefore, this research addresses the literature gap by identifying which performance objectives should be considered in the elaboration of route plans and how they relate to sustainability guidelines. It is noteworthy that no other study with a similar objective was identified in the literature.

Suggested Citation

  • Alice Vasconcelos Nobre & Caio Cézar Rodrigues Oliveira & Denilson Ricardo de Lucena Nunes & André Cristiano Silva Melo & Gil Eduardo Guimarães & Rosley Anholon & Vitor William Batista Martins, 2022. "Analysis of Decision Parameters for Route Plans and Their Importance for Sustainability: An Exploratory Study Using the TOPSIS Technique," Logistics, MDPI, vol. 6(2), pages 1-12, May.
    • Handle: RePEc:gam:jlogis:v:6:y:2022:i:2:p:32-:d:818994
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2305-6290/6/2/32/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2305-6290/6/2/32/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gendreau, Michel & Laporte, Gilbert & Seguin, Rene, 1996. "Stochastic vehicle routing," European Journal of Operational Research, Elsevier, vol. 88(1), pages 3-12, January.
    2. Shen, Zuo-Jun Max & Feng, Bo & Mao, Chao & Ran, Lun, 2019. "Optimization models for electric vehicle service operations: A literature review," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 462-477.
    3. Laporte, Gilbert, 1992. "The traveling salesman problem: An overview of exact and approximate algorithms," European Journal of Operational Research, Elsevier, vol. 59(2), pages 231-247, June.
    4. Richard Eglese & Sofoclis Zambirinis, 2018. "Disruption management in vehicle routing and scheduling for road freight transport: a review," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(1), pages 1-17, April.
    5. Richard Eglese & Sofoclis Zambirinis, 2018. "Rejoinder on: Disruption management in vehicle routing and scheduling for road freight transport: a review," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(1), pages 27-29, April.
    6. Vitor W. B. Martins & Rosley Anholon & Osvaldo L. G. Quelhas & Walter Leal Filho, 2019. "Sustainable Practices in Logistics Systems: An Overview of Companies in Brazil," Sustainability, MDPI, vol. 11(15), pages 1-12, July.
    7. Lorena Reyes-Rubiano & Laura Calvet & Angel A. Juan & Javier Faulin & Lluc Bové, 2020. "A biased-randomized variable neighborhood search for sustainable multi-depot vehicle routing problems," Journal of Heuristics, Springer, vol. 26(3), pages 401-422, June.
    8. M. Azizur Rahman & Al-Amin Hossain & Binoy Debnath & Zinnat Mahmud Zefat & Mohammad Sarwar Morshed & Ziaul Haq Adnan, 2021. "Intelligent Vehicle Scheduling and Routing for a Chain of Retail Stores: A Case Study of Dhaka, Bangladesh," Logistics, MDPI, vol. 5(3), pages 1-21, September.
    9. Brandt, Felix & Nickel, Stefan, 2019. "The air cargo load planning problem - a consolidated problem definition and literature review on related problems," European Journal of Operational Research, Elsevier, vol. 275(2), pages 399-410.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shih-Che Lo, 2022. "A Particle Swarm Optimization Approach to Solve the Vehicle Routing Problem with Cross-Docking and Carbon Emissions Reduction in Logistics Management," Logistics, MDPI, vol. 6(3), pages 1-15, September.
    2. Zhiqiang Liu & Yanqi Niu & Caiyun Guo & Shitong Jia, 2023. "A Vehicle Routing Optimization Model for Community Group Buying Considering Carbon Emissions and Total Distribution Costs," Energies, MDPI, vol. 16(2), pages 1-20, January.
    3. Vitor William Batista Martins & Denilson Ricardo de Lucena Nunes & André Cristiano Silva Melo & Rayra Brandão & Antônio Erlindo Braga Júnior & Verônica de Menezes Nascimento Nagata, 2022. "Analysis of the Activities That Make Up the Reverse Logistics Processes and Their Importance for the Future of Logistics Networks: An Exploratory Study Using the TOPSIS Technique," Logistics, MDPI, vol. 6(3), pages 1-17, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sun, Yanshuo & Kirtonia, Sajeeb & Chen, Zhi-Long, 2021. "A survey of finished vehicle distribution and related problems from an optimization perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    2. Giménez-Palacios, Iván & Parreño, Francisco & Álvarez-Valdés, Ramón & Paquay, Célia & Oliveira, Beatriz Brito & Carravilla, Maria Antónia & Oliveira, José Fernando, 2022. "First-mile logistics parcel pickup: Vehicle routing with packing constraints under disruption," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    3. Crainic, Teodor Gabriel & Laporte, Gilbert, 1997. "Planning models for freight transportation," European Journal of Operational Research, Elsevier, vol. 97(3), pages 409-438, March.
    4. Jafarian, Ahmad & Asgari, Nasrin & Mohri, Seyed Sina & Fatemi-Sadr, Elham & Farahani, Reza Zanjirani, 2019. "The inventory-routing problem subject to vehicle failure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 254-294.
    5. Lydia Novoszel & Tina Wakolbinger, 2022. "Meta-analysis of Supply Chain Disruption Research," SN Operations Research Forum, Springer, vol. 3(1), pages 1-25, March.
    6. Novaes, Antonio G. N. & Graciolli, Odacir D., 1999. "Designing multi-vehicle delivery tours in a grid-cell format," European Journal of Operational Research, Elsevier, vol. 119(3), pages 613-634, December.
    7. Margaretha Gansterer & Richard F. Hartl, 2020. "Shared resources in collaborative vehicle routing," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(1), pages 1-20, April.
    8. Marielle Christiansen & Kjetil Fagerholt, 2002. "Robust ship scheduling with multiple time windows," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(6), pages 611-625, September.
    9. Sahar Bsaybes & Alain Quilliot & Annegret K. Wagler, 2019. "Fleet management for autonomous vehicles using flows in time-expanded networks," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 288-311, July.
    10. Hazem Ali & Ting Chen & Yunhong Hao, 2021. "Sustainable Manufacturing Practices, Competitive Capabilities, and Sustainable Performance: Moderating Role of Environmental Regulations," Sustainability, MDPI, vol. 13(18), pages 1-19, September.
    11. Marcos Singer & Patricio Donoso & Natalia Jadue, 2004. "Evaluacion De Las Oportunidades De Mejoramiento De La Logistica Directa De Emergencia," Abante, Escuela de Administracion. Pontificia Universidad Católica de Chile., vol. 7(2), pages 179-209.
    12. Almeder, Christian & Hartl, Richard F., 2013. "A metaheuristic optimization approach for a real-world stochastic flexible flow shop problem with limited buffer," International Journal of Production Economics, Elsevier, vol. 145(1), pages 88-95.
    13. Novoa, Clara & Storer, Robert, 2009. "An approximate dynamic programming approach for the vehicle routing problem with stochastic demands," European Journal of Operational Research, Elsevier, vol. 196(2), pages 509-515, July.
    14. Hisham Alidrisi, 2021. "The Development of an Efficiency-Based Global Green Manufacturing Innovation Index: An Input-Oriented DEA Approach," Sustainability, MDPI, vol. 13(22), pages 1-11, November.
    15. Ann Melissa Campbell & Martin W. P. Savelsbergh, 2005. "Decision Support for Consumer Direct Grocery Initiatives," Transportation Science, INFORMS, vol. 39(3), pages 313-327, August.
    16. Tang, Lixin & Liu, Jiyin & Rong, Aiying & Yang, Zihou, 2000. "A multiple traveling salesman problem model for hot rolling scheduling in Shanghai Baoshan Iron & Steel Complex," European Journal of Operational Research, Elsevier, vol. 124(2), pages 267-282, July.
    17. Timothy M. Sweda & Irina S. Dolinskaya & Diego Klabjan, 2017. "Adaptive Routing and Recharging Policies for Electric Vehicles," Transportation Science, INFORMS, vol. 51(4), pages 1326-1348, November.
    18. Castellano, Davide & Gallo, Mosè & Grassi, Andrea & Santillo, Liberatina C., 2019. "The effect of GHG emissions on production, inventory replenishment and routing decisions in a single vendor-multiple buyers supply chain," International Journal of Production Economics, Elsevier, vol. 218(C), pages 30-42.
    19. Yossi Hadad & Baruch Keren & Dima Alberg, 2023. "An Expert System for Ranking and Matching Electric Vehicles to Customer Specifications and Requirements," Energies, MDPI, vol. 16(11), pages 1-18, May.
    20. Kafle, Nabin & Zou, Bo & Lin, Jane, 2017. "Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 62-82.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlogis:v:6:y:2022:i:2:p:32-:d:818994. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.