A comparative bus selection for intercity transportation with an integrated PIPRECIA &amp; COPRAS-G

Özdağoğlu, Aşkın; Öztaş, Gülin Zeynep; Keleş, Murat Kemal; Genç, Volkan

doi:10.1016/j.cstp.2022.03.012

Cited by 16 publications

(2 citation statements)

References 38 publications

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“…The complex proportional assessment (COPRAS) method, initially introduced in the 2004 paper titled "Housing credit access model: The case for Lithuania" [44], has since been widely applied in various research domains, as evidenced by studies [45][46][47][48][49][50]. Over time, the method has been enhanced by integrating theories adept at handling uncertainties and inaccuracies, such as Fuzzy [51][52][53][54], Rough [55][56][57][58], and Grey [59][60][61][62].…”

Section: Copras-g Methodsmentioning

confidence: 99%

Optimizing Military Decision-Making: Application of the FUCOM– EWAA–COPRAS-G MCDM Model

Tešić,

Božanić

2023

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In contemporary military contexts, the determination of an optimal course of action (COA) in combat operations emerges as a critical challenge. This study delineates a decision support methodology for military applications, employing sophisticated decision analysis techniques. The initial phase entails the identification of pivotal criteria for assessing and ranking COAs, followed by the assignment of weight coefficients to each criterion via the full consistency method (FUCOM). Subsequently, the Einstein weighted arithmetic average operator (EWAA) was utilized for the aggregation of expert opinions, ensuring a consensual evaluation of these criteria and culminating in the final values of their weight coefficients. The ensuing phase focuses on the selection of an optimal COA, incorporating the grey complex proportional assessment (COPRAS-G) method. This method addresses uncertainties and varying criterion values. Expert ratings were again aggregated using the EWAA operator. The findings from this phase are designed to provide military commanders with precise, data-driven guidance for decision-making. To validate and verify the stability of the proposed model, a series of tests were conducted, including a rank reversal test, sensitivity analysis regarding changes in weight coefficients, and a comparative analysis with alternative methods. These assessments uniformly indicated the model's consistency, stability, and validity as a military decision support tool. Emphasizing a high degree of confidence in COA selection, the methodology advocated herein is applicable to decision-making processes in the planning and execution of military operations. The uniform application of professional terms, consistent with the broader context of this research, ensures clarity and coherence in its presentation. The approach outlined in this study stands as a testament to rigorous analytical methodologies in the realm of military strategic planning, offering a robust framework for decision-making under conditions of uncertainty and complexity.

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Section: Copras-g Methodsmentioning

confidence: 99%

Optimizing Military Decision-Making: Application of the FUCOM– EWAA–COPRAS-G MCDM Model

Tešić,

Božanić

2023

ATAMS

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“…In Bosnia and Herzegovina, two areas have been designated as strict nature reserves (SNRs): SNR Prašuma Janj and SNR Prašuma Lom. Furthermore, the country is home to a total of four national parks, including National Park (NP) Kozara, NP Sutjeska, NP Una, and the most recently established NP [20] Advanced battery technologies selection MCDM-WPM Babar et al [21] Viability of EV in the current market Fuzzy SWOT, fuzzy LP Büyüközkan and Uztürk [22] Sustainable urban logistics SAW, VIKOR Hamurcu and Eren [23] Electric bus selection AHP, TOPSIS Khan et al [24] HEV selection TOPSIS Ziemba [25] EV selection for government use PROSA-C, Monte Carlo Ecer [26] Comprehensively assessing BEV alternatives SECA, MARCOS, MAIRCA, COCOSO, ARAS, COPRAS Khan and Ali [27] Smart waste management adoption framework Fuzzy SWARA, fuzzy VIKTOR Ren et al [28] Selection strategies for BEVs LDA, DEMATEL, DANP, VIKTOR Ziemba [29] Selection of city and compact EVs NEAT F-PROMETHEE Ziemba [30] Analysis and recommendation of the EV Monte Carlo, fuzzy TOPSIS, fuzzy SAW, NEAT F-PROMETHEE II Hamurcu and Eren [31] EV selection for transportation in inner city AHP, GP, TOPSIS He [32] Selection of battery electric bus EWM Oztaysi et al [33] EV selection problem F-SMART Ozdagoglu et al [34] Bus selection for intercity transportation PIPRECIA, COPRAS-G Stopka et al [35] Evaluation of selected passenger EVs AHP Štilić et al [36] Taxi service EV selection SWARA, MSDM, MABAC Wei and Zhou [37] EV supplier selection BWM, fuzzy VIKOR Ziemba and Gago [38] Selection and analysis of e-scooters PROMETHEE GDSS, GAIA Puška et al [39] EV selection DNMEREC, DNCRADIS Ba ˛czkiewicz and Wa ˛tróbski [40] EV selection Entropy, standard deviation (SD), CRITIC, Gini coefcient-based, MEREC, statistical variance, CILOS, IDOCRIW, VIKOR Dwivedi and Sharma [41] EV selection Entropy, TOPSIS Drina. In this research, the focus will be on creating a sustainable transportation system based on the selection of EVs for the needs of the NP Kozara.…”

Section: Methodsmentioning

confidence: 99%

Selection of EVs as Tourist and Logistic Means of Transportation in Bosnia and Herzegovina’s Nature Protected Areas Using Z-Number and Rough Set Modeling

Puška,

Štilić,

Božanić

et al. 2023

Discrete Dynamics in Nature and Society

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This research focuses on the use of electric vehicles (EVs) to transport visitors and cargo within Bosnia and Herzegovina’s Kozara National Park. Reduced air pollution and the preservation of natural resources are required to help protect this aerial spa. Together with the expert employees of this NP, the EV that would best suit their needs was chosen. The process of decision-making combines subjective and objective methods. Employees first chose the criteria and alternatives and then weighed their importance. On that occasion, Z-numbers were used to include uncertainty in the decision, because it is not always possible to make decisions with complete certainty. Furthermore, the weight of these criteria was determined using the fuzzy PIPRECIA (PIvot Pairwise Relative Criteria Importance Assessment) method. Range (C1) became the most important criterion, followed by vehicle cost (C2), and the technical specifications of these EVs were used to compare them. Because these specifications vary, a rough set was used in which the minimum and maximum EV characteristics were taken based on specific criteria. To rank the alternatives, the R-CRADIS (Rough Compromise Ranking of Alternatives with Distance to Ideal Solution) method was used. According to the research results, the Mercedes eVito Tourer 90 kWh is the highest ranked EV and the validation of the results confirmed these findings. According to the research results, the Mercedes eVito Tourer 90 kWh is the highest ranked EV and the validation of the results confirmed these findings. The sensitivity analysis revealed that if criterion C1 is not as important, the other EVs are ranked higher. This research`s methodology has demonstrated flexibility, therefore it is recommended for use in similar research.

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An integrated interval-valued Pythagorean fuzzy WISP approach for industry 4.0 technology assessment and digital transformation

Rani

Pamučar

Mishra³

et al. 2023

Ann Oper Res

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A comparative bus selection for intercity transportation with an integrated PIPRECIA & COPRAS-G

Cited by 16 publications

References 38 publications

Optimizing Military Decision-Making: Application of the FUCOM– EWAA–COPRAS-G MCDM Model

Optimizing Military Decision-Making: Application of the FUCOM– EWAA–COPRAS-G MCDM Model

Selection of EVs as Tourist and Logistic Means of Transportation in Bosnia and Herzegovina’s Nature Protected Areas Using Z-Number and Rough Set Modeling

An integrated interval-valued Pythagorean fuzzy WISP approach for industry 4.0 technology assessment and digital transformation

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