An intuitionistic fuzzy-based model for performance evaluation of EcoPorts

Yalçın, Galip Cihan; Kara, Karahan; Toygar, Arda; Simic, Vladimir; Pamucar, Dragan; Köleoğlu, Nilay

doi:10.1016/j.engappai.2023.107192

Cited by 7 publications

(3 citation statements)

References 67 publications

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“…In this paper, the authors have chosen to apply a novel multicriteria approach to solving the problem of selecting a sustainable delivery model, recently developed by Bošković et al [5]. Considering the method's relatively recent development, it has been applied to address several types of problems to date: an Intuitionistic Fuzzy model for assessing the performance of Eco Ports [13], an interval decision-making method of type-2 fuzzy AROMAN for enhancing the sustainability of postal networks in rural areas [14], a decision-making model for selecting professional drivers [15], and the evaluation of sustainable human resource management in manufacturing companies [16]. The results are presented in Table 2.…”

Section: Tablementioning

confidence: 99%

“…Overview of the applications of the AROMAN method in the literature References Tasks Bošković et al [5] Yalçın et al [13] Choosing an electric vehicle for delivery Model for assessing the performance of eco ports Nikolić et al [14] Improving the sustainability of the postal network in rural areas Čubranić-Dobrodolac et al [15] Selection of professional drivers Rani et al [16] Assessment of Sustainable HRM in manufacturing companies This paper Sustainable delivery model -choice of delivery mode…”

Section: Tablementioning

confidence: 99%

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Sustainable Delivery Model Selection using AROMAN Approach

Dobrodolac,

Bošković,

Jovčić

et al. 2024

Decis. Mak. Adv.

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The development of electronic commerce has resulted in an increase in the number of shipments in their transfer systems. Delivery companies strive to respond to emerging situations, meet customer needs, and achieve profit through the optimization of their operations. The imperative is to establish a delivery system that is in line with the principles of sustainable development. This paper defines the task of choosing a sustainable model for shipment delivery and proposes the AROMAN method for its resolution. The applicability of the proposed method is demonstrated by solving the defined task in the territory of the city of Belgrade.

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Section: Tablementioning

confidence: 99%

Section: Tablementioning

confidence: 99%

Sustainable Delivery Model Selection using AROMAN Approach

Dobrodolac,

Bošković,

Jovčić

et al. 2024

Decis. Mak. Adv.

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“…Considering the fact that the AROMAN method is relatively new, so far it has been applied in solving several types of problems: Intuitionistic fuzzy model for EcoPorts performance evaluation [19], interval type 2 decision-making method Fuzzy AROMAN for improving the sustainability of the postal network in rural areas [20], decision-making model for the selection of professional drivers [21], evaluation of sustainable human resource management in manufacturing firms [22].…”

Section: Introductionmentioning

confidence: 99%

MCDM-Based Wildfire Risk Assessment: A Case Study on the State of Arizona

Pishahang,

Jovcic,

Hashemkhani Zolfani

et al. 2023

Fire

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The increasing frequency of wildfires has posed significant challenges to communities worldwide. The effectiveness of all aspects of disaster management depends on a credible estimation of the prevailing risk. Risk, the product of a hazard’s likelihood and its potential consequences, encompasses the probability of hazard occurrence, the exposure of assets to these hazards, existing vulnerabilities that amplify the consequences, and the capacity to manage, mitigate, and recover from their consequences. This paper employs the multiple criteria decision-making (MCDM) framework, which produces reliable results and allows for the customization of the relative importance of factors based on expert opinions. Utilizing the AROMAN algorithm, the study ranks counties in the state of Arizona according to their wildfire risk, drawing upon 25 factors categorized into expected annual loss, community resilience, and social vulnerability. A sensitivity analysis demonstrates the stability of the results when model parameters are altered, reinforcing the robustness of this approach in disaster risk assessment. While the paper primarily focuses on enhancing the safety of human communities in the context of wildfires, it highlights the versatility of the methodology, which can be applied to other natural hazards and accommodate more subjective risk and safety assessments.

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