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Neural Computing and ApplicationsVolume 31, Issue 9, 1 September 2019, Pages 5045-5068

New multi-criteria LNN WASPAS model for evaluating the work of advisors in the transport of hazardous goods(Article)

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  • aDepartment of Logistics, Military Academy, University of Defence in Belgrade, Pavla Jurisica Sturma 33, Belgrade, 11000, Serbia
  • bFaculty of Technical Sciences, University of Novi Sad, Trg Dositeja Obradovica 6, Novi Sad, 21000, Serbia
  • cFaculty of Transport and Traffic Engineering, University of East Sarajevo, Vojvode Mišića 52, Doboj, 74000, Bosnia and Herzegovina
  • dProvincial Secretariat for Energy, Construction and Transport, Autonomous Province of Vojvodina, Novi Sad, Serbia

Abstract

Successfully organizing the transport of hazardous materials and handling them correctly is a very important logistical task that affects both the overall flow of transport and the environment. Safety advisors for the transport of hazardous materials have a very important role to play in the proper and safe development of the transport flow for these materials; their task is primarily to use their knowledge and effort to prevent potential accidents from happening. In this research, a total of 21 safety advisors for the transport of hazardous materials in Serbia are assessed using a new model that integrates Linguistic Neutrosophic Numbers (LNN) and the WASPAS (Weighted Aggregated Sum Product Assessment) method. In this way, two important contributions are made, namely a completely new methodology for assessing the work of advisors and the new LNN WASPAS model, which enriches the field of multi-criteria decision making. The advisors are assessed by seven experts on the basis of nine criteria. After performing a sensitivity analysis on the results, validation of the model is carried out. The results obtained by the LNN WASPAS model are validated by comparing them with the results obtained by LNN extensions of the TOPSIS (Technique for Order Performance by Similarity to Ideal Solution), LNN CODAS (COmbinative Distance-based ASsessment), LNN VIKOR (Multi-criteria Optimization and Compromise Solution) and LNN MABAC (Multi-Attributive Border Approximation area Comparison) models. The LNN CODAS, LNN VIKOR and LNN MABAC are also further developed in this study, which is an additional contribution made by the paper. After the sensitivity analysis, the SCC (Spearman Correlation Coefficient) is calculated which confirms the stability of the previously obtained results. © 2019, Springer-Verlag London Ltd., part of Springer Nature.

Author keywords

Hazardous goodsLinguistic neutrosophic numbersMulti-criteria decision makingWASPAS

Indexed keywords

Engineering controlled terms:Decision makingHazardous materialsHazardsLinguisticsMaterials handlingMultiobjective optimization
Engineering uncontrolled termsHazardous goodsIdeal solutionsMulti criteria decision makingMulti-criteriaMulticriteria optimizationSpearman correlation coefficientsTransport flowWASPAS
Engineering main heading:Sensitivity analysis

Funding details

Funding sponsor Funding number Acronym
Serbia
Ministry of DefenceMOD
Ministry of Education, Science and TechnologyMEST
  • 1

    The work reported in this paper is a part of the investigation within the research projects TR 36017 and VA-TT/4/17-19 supported by the Ministry for Science and Technology (Republic of Serbia), Ministry of Defence (Republic of Serbia) and the University of defence in Belgrade. This support is gratefully acknowledged.

  • ISSN: 09410643
  • Source Type: Journal
  • Original language: English
  • DOI: 10.1007/s00521-018-03997-7
  • Document Type: Article
  • Publisher: Springer London

  Pamučar, D.; Department of Logistics, Military Academy, University of Defence in Belgrade, Pavla Jurisica Sturma 33, Belgrade, Serbia;
© Copyright 2019 Elsevier B.V., All rights reserved.

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