Višekriterijumski BWM-COPRAS model za izbor optimalnog terenskog vozila za prevoz putnika

  • Dragan S. Pamučar Univerzitet odbrane u Beogradu, Vojna akademija
  • Lazar M. Savin Univerzitet odbrane u Beogradu, Vojna akademija
Ključne reči: BWM||, ||BWM, COPRAS||, ||COPRAS, MABAC||, ||MABAC, MAIRCA||, ||MAIRCA, vehicle selection||, ||izbor vozila, multi-criteria decision making||, ||donošenje višekriterijumskih odluka,

Sažetak


Uvod/cilj: Adekvatna evaluacija i izbor terenskog vozila za izvršenje različitih vrsta zadataka veoma je važan faktor koji utiče na mobilnost korisnika, njihovu bezbednost, kao i na kvalitet i efikasnost izvršavanja transportnih aktivnosti u Vojsci Srbije (VS).

Metode: Stoga je za izbor optimalnog terenskog vozila za potrebe VS, u ovom radu predložen BWM (Best Worst Method) i COPRAS (Compressed Proportional Assessment) model . Određivanje relativnih težina kriterijuma,  na osnovu kojih se vrši vrednovanje potencijalnih terenskih vozila, izvršeno je primenom BWM metode. Pored COPRAS metode, koja je sastavni deo osnovnog modela za donošenje odluke, u ovom radu su, kroz validaciju rezultata, primenjene i metode MABAC (MultiAttributive Border Approximation area Comparison) i MAIRCA (MultiAtributive Ideal-Real Comparative Analysis).

Rezultati: Testiranjem BWM-COPRAS modela na primeru izbora optimalnog terenskog vozila u VS dobijena je visoka korelacija rangova. Validacija rezultata izvršena je statističkom obradom rezultata dobijenih različitim višekriterijumskim tehnikama, primenom Spirmanovog koeficijenta korelacije.

Zaključak: Rezultati pokazuju stabilnost rezultata predloženog modela u rangiranju alternativa i dokazuju njegovu primenjivost za rešavanje višekriterijumskih problema.

Biografije autora

Dragan S. Pamučar, Univerzitet odbrane u Beogradu, Vojna akademija

Doktor nauka

Lazar M. Savin, Univerzitet odbrane u Beogradu, Vojna akademija
University of defence, Military academy, Serbia

Reference

Awasthi, A., & Chauhan, S.S. 2011. Using AHP and Dempster–Shafer theory for evaluating sustainable transport solutions. Environmental Modelling and Software, 26(6), pp.787-796. Available at: https://doi.org/10.1016/j.envsoft.2010.11.010.

Awasthi, A., & Chauhan, S.S. 2012. A hybrid approach integrating Affinity Diagram, AHP and fuzzy TOPSIS for sustainable city logistics planning. Applied Mathematical Modelling, 36(2), pp.573-584. Available at: https://doi.org/10.1016/j.apm.2011.07.033.

Awasthi, A., Chauhan, S.S., & Omrani, H. 2011. Application of fuzzy TOPSIS in evaluating sustainable transportation systems. Expert Systems with Applications, 38(10), pp.12270-12280. Available at: https://doi.org/10.1016/j.eswa.2011.04.005.

Badi, I.A., Abdulshahed, A.M., & Shetwan, A.G. 2018. A Case Study Of Supplier Selection For A Steelmaking Company In Libya By Using The Combinative Distance-Based Assessment (Codas) Model. Decision Making: Applications in Management and Engineering, 1(1), pp.1-12. Available at: https://doi.org/10.31181/dmame180101b.

Badi, I., & Ballem, M. 2018. Supplier Selection using Rough BWM-MAIRCA model: A case study in Pharmaceutical Supplying in Libya. Decision Making: Applications in Management and Engineering, 1(2) [online]. Available at: https://www.dmame.org/index.php/dmame/article/view/12/11. [Accessed: 21 August 2019]

Barić, D., Pilko, H., & Strujić, J. 2016. An Analytic Hierarchy Process Model To Evaluate Road Section Design. Transport, 31(3), pp.312-321. Available at: https://doi.org/10.3846/16484142.2016.1157830.

Bojković, N., Anić, I., & Pejčić-Tarle, S. 2010. One solution for cross-country transport-sustainability evaluation using a modified ELECTRE method. Ecological Economics, 69(5), pp.1176-1186. Available at: https://doi.org/10.1016/j.ecolecon.2010.01.006.

Cadena, P.C.B., & Magro, J.M.V. 2015. Setting The Weights Of Sustainability Criteria For The Appraisal Of Transport Projects. Transport, 30(3), pp.298-306. Available at: https://doi.org/10.3846/16484142.2015.1086890.

Castillo, H., & Pitfield, D.E. 2010. ELASTIC – A methodological framework for identifying and selecting sustainable transport indicators. Transportation Research Part D: Transport and Environment, 15(4), pp.179-188. Available at: https://doi.org/10.1016/j.trd.2009.09.002.

Chatterjee, K., Pamucar, D., & Zavadskas, E.K. 2018. Evaluating the performance of suppliers based on using the R'AMATEL-MAIRCA method for green supply chain implementation in electronics industry. Journal of Cleaner Production, 184, pp.101-129. Available at: https://doi.org/10.1016/j.jclepro.2018.02.186.

Dimić, S., Pamučar, D., Ljubojević, S., & Đorović, B. 2016. Strategic Transport Management Models—The Case Study of an Oil Industry. Sustainability, 8(9), p.954. Available at: https://doi.org/10.3390/su8090954.

Fazlollahtabar, H. 2018. Operations and inspection Cost minimization for a reverse supply chain, Operational Research in Engineering Sciences: Theory and Applications, 1(1), pp.91-107 [online]. Available at: http://www.oresta.org/index.php/oresta/article/view/8/8. [Accessed: 21 August 2019]

Fazlollahtabar, H., Smailbašić, A., & Stević, Ž. 2019. FUCOM method in group decision-making: Selection of forklift in a warehouse. Decision Making: Applications in Management and Engineering, 2(1), pp.49-65 [online]. Available at: https://www.dmame.org/index.php/dmame/article/view/26/24. [Accessed: 21 August 2019]

Inti, S., & Tandon, V. 2017. Application of Fuzzy Preference–Analytic Hierarchy Process Logic in Evaluating Sustainability of Transportation Infrastructure Requiring Multicriteria Decision Making. Journal of Infrastructure Systems, 23(4), p.4017014. Available at: https://doi.org/10.1061/(asce)is.1943-555x.0000373.

Jeon, C.M., Amekudzi, A.A., & Guensler, R.L. 2010. Evaluating Plan Alternatives for Transportation System Sustainability: Atlanta Metropolitan Region. International Journal of Sustainable Transportation, 4(4), pp.227-247.

Jiang, P., Hu, Y., Yen, G., Jiang, H., & Chiu, Y. 2018. Using a Novel Grey DANP Model to Identify Interactions between Manufacturing and Logistics Industries in China. Sustainability, 10(10), p.3456. Available at: https://doi.org/10.3390/su10103456.

Jones, S., Tefe, M., & Appiah-Opoku, S. 2013. Proposed framework for sustainability screening of urban transport projects in developing countries: A case study of Accra, Ghana. Transportation Research Part A: Policy and Practice, 49, pp.21-34. Available at: https://doi.org/10.1016/j.tra.2013.01.003.

Kahraman, Y.R. 2002. Robust sensitivity analysis for multi-attribute deterministic hierarchical value models.Ohio: Storming Media.

Kirkwood, C.W. 1997. Strategic decision making: Multi-objective decision analysis with Spreadsheets.Belmont: Duxbury Press.

López, E., & Monzón, A. 2010. Integration of Sustainability Issues in Strategic Transportation Planning: A Multi-criteria Model for the Assessment of Transport Infrastructure Plans. Computer-Aided Civil and Infrastructure Engineering, 25(6), pp.440-451. Available at: https://doi.org/10.1111/j.1467-8667.2010.00652.x.

Mavi, R.K., Goh, M., & Zarbakhshnia, N. 2017. Sustainable third-party reverse logistic provider selection with fuzzy SWARA and fuzzy MOORA in plastic industry. The International Journal of Advanced Manufacturing Technology, 91(5-8), pp.2401-2418. Available at: https://doi.org/10.1007/s00170-016-9880-x.

Mitropoulos, L.K., & Prevedouros, P.D. 2016. Incorporating sustainability assessment in transportation planning: an urban transportation vehicle-based approach. Transportation Planning and Technology, 39(5), pp.439-463. Available at: https://doi.org/10.1080/03081060.2016.1174363.

Mukhametzyanov, I., & Pamučar, D. 2018. A Sensitivity analysis in MCDM problems: A statistical approach. Decision Making: Applications in Management and Engineering, 1(2) [online]. Available at: https://www.dmame.org/index.php/dmame/article/view/14/14. [Accessed: 21 August 2019]

Noureddine, M., & Ristic, M. 2019. Route planning for hazardous materials transportation: Multicriteria decision making approach. Decision Making: Applications in Management and Engineering, 2(1), pp.66-85 [online]. Availabele at: https://www.dmame.org/index.php/dmame/article/view/29/25. [Accessed: 21 August 2019]

Nunić, Z. 2018. Evaluation and selection of the PVC carpentry Manufacturer using the FUCOM-MABAC model. Operational Research in Engineering Sciences: Theory and Applications, 1(1), pp.13-28 [online]. Available at: https://www.oresta.org/index.php/oresta/article/view/3/3. [Accessed: 21 August 2019]

Pamučar, D., Badi, I., Sanja, K., & Obradović, R. 2018a. A Novel Approach for the Selection of Power-Generation Technology Using a Linguistic Neutrosophic CODAS Method: A Case Study in Libya. Energies, 11(9), p.2489. Available at: https://doi.org/10.3390/en11092489.

Pamučar, D., & Ćirović, G. 2015. The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Systems with Applications, 42(6), pp.3016-3028. Available at: https://doi.org/10.1016/j.eswa.2014.11.057.

Pamučar, D., Lukovac, V., Božanić, D., Komazec, N. 2018b. Multi-criteria FUCOM-MAIRCA model for the evaluation of level crossings: case study in the Republic of Serbia. Operational Research in Engineering Sciences: Theory and Applications, 1(1), pp.108-129 [online]. Available at: http://www.oresta.org/index.php/oresta/article/view/10/9. [Accessed: 21 August 2019]

Pamučar, D., Lukovac, V., & Pejčić-Tarle, S. 2013. Application Of Adaptive Neuro Fuzzy Inference System In The Process Of Transportation Support. Asia-Pacific Journal of Operational Research, 30(02), p.1250053. Available at: https://doi.org/10.1142/s0217595912500534.

Pamučar, D., Sremac, S., Stević, Ž., Ćirović, G., & Tomić, D. 2019. New multi-criteria LNN WASPAS model for evaluating the work of advisors in the transport of hazardous goods. Neural Computing and Applications, 31(9), pp.5045-5068. Available at: https://doi.org/10.1007/s00521-018-03997-7

Pamucar, D.S., Tarle, S.P., & Parezanovic, T. 2018a. New hybrid multi-criteria decision-making DEMATEL-MAIRCA model: Sustainable selection of a location for the development of multimodal logistics centre. Economic Research/Ekonomska Istraživanja, 31(1), pp.1641-1665.

Pamučar, D., Vasin, L., Atanasković, P., & Miličić, M. 2016. Planning the City Logistics Terminal Location by Applying the Green p -Median Model and Type-2 Neurofuzzy Network. Computational Intelligence and Neuroscience, , pp.1-15. Available at: https://doi.org/10.1155/2016/6972818.

Puška, A., Maksimović, A., Stojanović, I. 2018. Improving organizational learning by sharing information through innovative supply chain in agro-food companies from Bosnia and Herzegovina. Operational Research in Engineering Sciences: Theory and Applications, 1(1), pp.76-90 [online]. Available at: http://www.oresta.org/index.php/oresta/article/view/7/7. [Accessed: 21 August 2019]

Radović, D., Stević, Ž., Pamučar, D., Zavadskas, E., Badi, I., Antuchevičiene, J., & Turskis, Z. 2018. Measuring Performance in Transportation Companies in Developing Countries: A Novel Rough ARAS Model. Symmetry, 10(10), p.434. Available at: https://doi.org/10.3390/sym10100434.

Rao, C., Goh, M., Zhao, Y., & Zheng, J. 2015. Location selection of city logistics centers under sustainability. Transportation Research Part D: Transport and Environment, 36, pp.29-44. Available at: https://doi.org/10.1016/j.trd.2015.02.008.

Rezaei, J. 2015. Best-worst multi-criteria decision-making method. Omega, 53(June), pp.49-57. Available at: https://doi.org/10.1016/j.omega.2014.11.009.

Safaei Mohamadabadi, H.S., Tichkowsky, G., & Kumar, A. 2009. Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles. Energy, 34(1), pp.112-125. Available at: https://doi.org/10.1016/j.energy.2008.09.004.

Simongáti, G. 2010. Multi-Criteria Decision Making Support Tool For Freight Integrators: Selecting The Most Sustainable Alternative. Transport, 25(1), pp.89-97. Available at: https://doi.org/10.3846/transport.2010.12.

Sremac, S., Stević, Ž., Pamučar, D., Arsić, M., & Matić, B. 2018. Evaluation of a Third-Party Logistics (3PL) Provider Using a Rough SWARA–WASPAS Model Based on a New Rough Dombi Agregator. Symmetry, 10(8), p.305. Available at: https://doi.org/10.3390/sym10080305.

Stanković, M., Gladović, P., & Popović, V. 2019. Determining the importance of the criteria of traffic accessibility using fuzzy AHP and rough AHP method. Decision Making: Applications in Management and Engineering, 2(1), pp.86-104 [online]. Available at: https://www.dmame.org/index.php/dmame/article/view/27/26. [Accessed: 21 August 2019]

Stanujkić, D., & Karabašević, D. 2018. An extension of the WASPAS method for decision-making problems with intuitionistic fuzzy numbers: a case of website evaluation. Operational Research in Engineering Sciences: Theory and Applications, 1(1), pp.29-39 [online]. Available at: http://www.oresta.org/index.php/oresta/article/view/4/4. [Accessed: 21 August 2019]

Starcevic, S., Bojovic, N., Skrickij, V., & Junevičius, R. 2019. AHP method and data envelopment analysis application in terrain vehicle selection for the purposes of military units engagement in multinational operations. Transport, in press.

Stević, Ž., Pamučar, D., Kazimieras, Z.E., Ćirović, G., & Prentkovskis, O. 2017. The Selection of Wagons for the Internal Transport of a Logistics Company: A Novel Approach Based on Rough BWM and Rough SAW Methods. Symmetry, 9(11), p.264. Available at: https://doi.org/10.3390/sym9110264.

Stević, Ž., Pamučar, D., Subotić, M., Antuchevičiene, J., & Zavadskas, E.K. 2018. The Location Selection for Roundabout Construction Using Rough BWM-Rough WASPAS Approach Based on a New Rough Hamy Aggregator. Sustainability, 10(8), p.2817. Available at: https://doi.org/10.3390/su10082817.

Turskis, Z., & Zavadskas, E.K. 2010. A New Fuzzy Additive Ratio Assessment Method (Aras‐F). Case Study: The Analysis Of Fuzzy Multiple Criteria In Order To Select The Logistic Centers Location. Transport, 25(4), pp.423-432. Available at: https://doi.org/10.3846/transport.2010.52.

Wang, H., Jiang, Z., Zhang, H., Wang, Y., Yang, Y., & Li, Y. 2018. An integrated MCDM approach considering demands-matching for reverse logistics. Journal of Cleaner Production, 208, pp.199-210. Available at: https://doi.org/10.1016/j.jclepro.2018.10.131.

Zavadskas, E.K., & Kaklauskas, A. 1996. Multiple Criteria Evaluation of Buildings. Vilnius: Technika (in Lithuanian).

Zečević, S., Tadić, S., & Krstić, M. 2017. Intermodal Transport Terminal Location Selection Using a Novel Hybrid MCDM Model. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 25(06), pp.853-876. Available at: https://doi.org/10.1142/s0218488517500362.

Objavljeno
2019/12/06
Rubrika
Originalni naučni radovi