Selecting a Cargo Aircraft for Humanitarian and Disaster Relief Operations by Multicriteria Decision Aid Methods

Gavião, Luiz Octávio; Sant’Anna, Annibal Parracho; Lima, Gílson Brito Alves; Garcia, Pauli Adriano de Almada; Kostin, Sergio; Asrilhant, Boris

doi:10.1109/tem.2019.2956356

Cited by 9 publications

(5 citation statements)

References 10 publications

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“…the data of 18 matrices). 49 Suppose a triangular fuzzy number A ~ with parameters ( l , m , u ) , then its membership function can be expressed as 50 :…”

Section: Methodsmentioning

confidence: 99%

Assessing the investment environment in container terminals: A knowledge gap model

Hsu

Huynh

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part M:

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This paper aims to evaluate the investment environment in container terminals (CTs) in one seaport from the attitudes of both terminal operators (TOs) and port companies (PCs). Evaluation criteria (ECs) regarding the investment environment in CTs are first created based on the prior literature and the CTs’ operational characteristics. A knowledge gap model based on an improved fuzzy AHP approach is then developed to assess the perceived differences on the ECs between TOs and PCs, by which the PCs managers could formulate practical policies to improve their investment environment in CTs. As an empirical study, the Taiwan International Port Corporation (TIPC) and its terminal operators in Kaohsiung port are examined to verify the research model. Results indicate that ECs with higher knowledge gap for TIPC include: Intra-port coopetition, Number of shipping carriers, and Business tax. Based on the result, theoretical and managerial implications are discussed.

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“…the data of 18 matrices). 49 Suppose a triangular fuzzy number A ~ with parameters ( l , m , u ) , then its membership function can be expressed as 50 :…”

Section: Methodsmentioning

confidence: 99%

Assessing the investment environment in container terminals: A knowledge gap model

Hsu

Huynh

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part M:

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“…The two subsequent stages of CPP remain unchanged and are described in detail in several published articles and books, with a wide range of applications, including sports science [35], management systems [43,44], security and defense [45], public health and social assistance [46,47], risk management [48], and bioenergy processes [36].…”

Section: Methodsmentioning

confidence: 99%

Composition of Probabilistic Preferences in Multicriteria Problems with Variables Measured in Likert Scales and Fitted by Empirical Distributions

Gavião¹,

Sant’Anna

Lima

et al. 2023

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The aim of this article is to demonstrate the advantages of the Composition of Probabilistic Preferences method in multicriteria problems with data from Likert scales. Multicriteria decision aids require a database as a decision matrix, in which two or more alternatives are evaluated according to two or more variables selected as decision criteria. Several problems of this nature use measures by Likert scales. Depending on the method, parameters from these data (e.g., means, modes or medians) are required for calculations. This parameterization of data in ordinal scales has fueled controversy for decades between authors who favor mathematical/statistical rigor and argue against the procedure, stating that ordinal scales should not be parameterized, and scientists from other areas who have shown gains from the process that compensates for this relaxation. The Composition of Probabilistic Preferences can allay the protests raised and obtain more accurate results than descriptive statistics or parametric models can bring. The proposed algorithm in R-code involves the use of probabilities with empirical distributions and fitting histograms of data measured by Likert scales. Two case studies with simulated datasets having peculiar characteristics and a real case illustrate the advantages of the Composition of Probabilistic Preferences.

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“…Before generating the matrix M', described in Equation ( 6), the evaluations of the initial decision matrix (M) are converted into probabilities, based on the Composition of Probabilistic Preferences (CPP) (Sant'Anna, 2015). This multicriteria decision support method has been widely explored in operations research for the solution of problems involving uncertainty in relation to the database, either due to the imprecision of the sources or the collection process, the variance of the performance of the alternatives in the face of different scenarios, among other aspects that allow assuming that the evaluations of the alternatives are not exact and constant values (Gavião et al, 2020(Gavião et al, , 2021.…”

Section: Function "Ahpperfprob"mentioning

confidence: 99%

Decision support based on performance data using the analytic hierarchy process without expert judgement

Gavião,

Lima,

Garcia

et al. 2024

BJO&PM

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Goal: This article proposes a decision model based on the Analytic Hierarchy Process that allows carrying out the evaluation of alternatives in a multicriteria problem, without expert judgement. Design / Methodology / Approach: The algorithm is based on AHP. The novelty is the transformation of a performance data matrix into pairwise evaluation matrices, instead of using experts’ judgement. Results: The algorithm was applied in a defense procurement problem for the choice of a light 4x4 vehicle for amphibious operations. The results allowed ranking the 17 models based on catalog data. Limitations of the investigation: the algorithm depends on the availability of catalog data, not always available in open sources in the defense industry. Practical implications: Decision support involves several activities in Operations Management and AHP has been frequently applied to solve problems in this sector. The proposed algorithm allows performing deterministic or probabilistic evaluations, depending on the degree of uncertainty and precision involving the systems’ performance data. These assessments are composed of scenarios to facilitate decision making. Originality / Value: AHP typically uses experts for pairwise judgments. However, human judgment is subject to outcomes that involve bias and cognitive distortions. Few studies have modeled the AHP without experts, even so they used human judgment in some part of the process. The approach proposed here does not require human judgment and returns two different results, based on the database precision. This new approach gives decision makers a different perspective and can alter the final choice.

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Selecting a Cargo Aircraft for Humanitarian and Disaster Relief Operations by Multicriteria Decision Aid Methods

Cited by 9 publications

References 10 publications

Assessing the investment environment in container terminals: A knowledge gap model

Assessing the investment environment in container terminals: A knowledge gap model

Composition of Probabilistic Preferences in Multicriteria Problems with Variables Measured in Likert Scales and Fitted by Empirical Distributions

Decision support based on performance data using the analytic hierarchy process without expert judgement

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