IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2021i1p223-d713911.html
   My bibliography  Save this article

Path Selection for the Inspection Robot by m-Generalized q-Neutrosophic PROMETHEE Approach

Author

Listed:
  • Romualdas Bausys

    (Department of Graphical Systems, Vilnius Gediminas Technical University, Sauletekio Ave. 11, LT-10223 Vilnius, Lithuania)

  • Edmundas Kazimieras Zavadskas

    (Institute of Sustainable Construction, Vilnius Gediminas Technical University, Sauletekio Ave. 11, LT-10223 Vilnius, Lithuania)

  • Rokas Semenas

    (Department of Graphical Systems, Vilnius Gediminas Technical University, Sauletekio Ave. 11, LT-10223 Vilnius, Lithuania)

Abstract

Path planning can be considered the most vital task of the autonomous robot. In this task, selecting an optimal route from the starting to the target position becomes an important problem that must be addressed when multiple competing optimization priorities are considered. Thus, a novel route assessment strategy based on a multi-criteria decision-making approach is proposed. The m-generalized q-neutrosophic PROMETHEE (PROMETHEE-mGqNS) method is applied to aggregate the competing route assessment requirements and choose an optimal route. A case study is investigated to explain the proposed strategy for path planning in a typical environment and indicates the method stability when incomplete input data characteristics are present.

Suggested Citation

  • Romualdas Bausys & Edmundas Kazimieras Zavadskas & Rokas Semenas, 2021. "Path Selection for the Inspection Robot by m-Generalized q-Neutrosophic PROMETHEE Approach," Energies, MDPI, vol. 15(1), pages 1-12, December.
    • Handle: RePEc:gam:jeners:v:15:y:2021:i:1:p:223-:d:713911
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/1/223/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/1/223/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fragapane, Giuseppe & de Koster, René & Sgarbossa, Fabio & Strandhagen, Jan Ola, 2021. "Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda," European Journal of Operational Research, Elsevier, vol. 294(2), pages 405-426.
    Full references (including those not matched with items on IDEAS)

    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. Chen, Wanying & Gong, Yeming & Chen, Qi & Wang, Hongwei, 2024. "Does battery management matter? Performance evaluation and operating policies in a self-climbing robotic warehouse," European Journal of Operational Research, Elsevier, vol. 312(1), pages 164-181.
    2. Tadumadze, Giorgi & Wenzel, Julia & Emde, Simon & Weidinger, Felix & Elbert, Ralf, 2023. "Assigning orders and pods to picking stations in a multi-level robotic mobile fulfillment system," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 136885, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Ranaboldo, M. & Aragüés-Peñalba, M. & Arica, E. & Bade, A. & Bullich-Massagué, E. & Burgio, A. & Caccamo, C. & Caprara, A. & Cimmino, D. & Domenech, B. & Donoso, I. & Fragapane, G. & González-Font-de-, 2024. "A comprehensive overview of industrial demand response status in Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 203(C).
    4. Cui, Yibing & Hu, Wei & Rahmani, Ahmed, 2023. "Fractional-order artificial bee colony algorithm with application in robot path planning," European Journal of Operational Research, Elsevier, vol. 306(1), pages 47-64.
    5. Weckenborg, Christian & Schumacher, Patrick & Thies, Christian & Spengler, Thomas S., 2024. "Flexibility in manufacturing system design: A review of recent approaches from Operations Research," European Journal of Operational Research, Elsevier, vol. 315(2), pages 413-441.
    6. Hu, Yue & Yang, Hongbing & Huang, Yi, 2022. "Conflict-free scheduling of large-scale multi-load AGVs in material transportation network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    7. Boccia, Maurizio & Masone, Adriano & Sterle, Claudio & Murino, Teresa, 2023. "The parallel AGV scheduling problem with battery constraints: A new formulation and a matheuristic approach," European Journal of Operational Research, Elsevier, vol. 307(2), pages 590-603.
    8. Lu Zhen & Jingwen Wu & Haolin Li & Zheyi Tan & Yingying Yuan, 2023. "Scheduling multiple types of equipment in an automated warehouse," Annals of Operations Research, Springer, vol. 322(2), pages 1119-1141, March.
    9. Yue Chen & Yisong Li, 2024. "Storage Location Assignment for Improving Human–Robot Collaborative Order-Picking Efficiency in Robotic Mobile Fulfillment Systems," Sustainability, MDPI, vol. 16(5), pages 1-25, February.
    10. Dukkanci, Okan & Campbell, James F. & Kara, Bahar Y., 2024. "Facility location decisions for drone delivery: A literature review," European Journal of Operational Research, Elsevier, vol. 316(2), pages 397-418.
    11. Mohamed Amjath & Laoucine Kerbache & James MacGregor Smith, 2024. "A Closed Queueing Networks Approach for an Optimal Heterogeneous Fleet Size of an Inter-Facility Bulk Material Transfer System," Logistics, MDPI, vol. 8(1), pages 1-38, March.
    12. Lihle N. Tikwayo & Tebello N. D. Mathaba, 2023. "Applications of Industry 4.0 Technologies in Warehouse Management: A Systematic Literature Review," Logistics, MDPI, vol. 7(2), pages 1-19, April.
    13. Pfrommer, Jakob & Meyer, Anne & Tierney, Kevin, 2024. "Solving the unit-load pre-marshalling problem in block stacking storage systems with multiple access directions," European Journal of Operational Research, Elsevier, vol. 313(3), pages 1054-1071.
    14. Mona Haji & Frank Himpel, 2024. "Building Resilience in Food Security: Sustainable Strategies Post-COVID-19," Sustainability, MDPI, vol. 16(3), pages 1-18, January.
    15. MA, Yunfeng & CHEN, Haoxun & YU, Yugang, 2022. "An efficient heuristic for minimizing the number of moves for the retrieval of a single item in a puzzle-based storage system with multiple escorts," European Journal of Operational Research, Elsevier, vol. 301(1), pages 51-66.
    16. Fontes, Dalila B.M.M. & Homayouni, S. Mahdi & Gonçalves, José F., 2023. "A hybrid particle swarm optimization and simulated annealing algorithm for the job shop scheduling problem with transport resources," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1140-1157.
    17. Agnieszka Deja & Tygran Dzhuguryan & Lyudmyla Dzhuguryan & Oleg Konradi & Robert Ulewicz, 2021. "Smart Sustainable City Manufacturing and Logistics: A Framework for City Logistics Node 4.0 Operations," Energies, MDPI, vol. 14(24), pages 1-21, December.
    18. Lechardoy, Lucie & López Forés, Laura & Codagnone, Cristiano, 2023. "Artificial intelligence at the workplace and the impacts on work organisation, working conditions and ethics," 32nd European Regional ITS Conference, Madrid 2023: Realising the digital decade in the European Union – Easier said than done? 277997, International Telecommunications Society (ITS).
    19. Snežana Tadić & Mladen Krstić & Svetlana Dabić-Miletić & Mladen Božić, 2023. "Smart Material Handling Solutions for City Logistics Systems," Sustainability, MDPI, vol. 15(8), pages 1-26, April.
    20. Matthias Thürer & Mark Stevenson, 2021. "Material handling and order release control in high-variety make-to-order shops: an assessment by simulation," Operations Management Research, Springer, vol. 14(3), pages 494-506, December.

    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:jeners:v:15:y:2021:i:1:p:223-:d:713911. 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.