GeoClust: Feature engineering based framework for location-sensitive disaster event detection using AHP-TOPSIS

Rani, Monika; Kaushal, Sakshi

doi:10.1016/j.eswa.2022.118461

Cited by 9 publications

(2 citation statements)

References 36 publications

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“…The result of this study showed that AHP-VIKOR, AHP-TOPSIS, and AHP-PROMETHEE have a greater correlation compared to AHP-MOORA and AHP-ELECTRE. Rani and Kaushal [28] agreed to apply AHP-TOPSIS for location-sensitive disaster event detection. Cihan et al, [29] used AHP and TOPSIS methods to solve the planned echocardiography device selection problem.…”

Section: Classification and Applications Of The Multi-criteria Decisi...mentioning

confidence: 99%

Decision-Making Support in Vehicle Routing Problems: A Review of Recent Literature

Syazwani Zainal Abidin,

Nor Izzati Zainal Abidin,

Hanita Daud

2024

ARASET

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The Vehicle Routing Problem (VRP) involves a set of customers with known locations, each having a certain demand for goods or services. There is also a fleet of vehicles available, each with limited capacity and often a fixed starting point. With the aid of mathematical programming tools, this paper offers an overview of the most recent VRP research. This study also examines the algorithms for solving VRP models and categorizes them in terms of their application areas. For these reasons, related publications that appeared in the international journal have been compiled and studied. According to the literature review, multi-criteria decision-making (MCDM) techniques have yet to constitute the most mathematical programming methods used to solve the VRP problem.

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Section: Classification and Applications Of The Multi-criteria Decisi...mentioning

confidence: 99%

Decision-Making Support in Vehicle Routing Problems: A Review of Recent Literature

Syazwani Zainal Abidin,

Nor Izzati Zainal Abidin,

Hanita Daud

2024

ARASET

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“…Various multi-attribute decision-making methods have been developed to solve decision problems involving TPIGN; among these, the technique for order preference by similarity to an ideal solution (TOPSIS) method is a classical and widely used approach (Yang et al , 2022a; Chae et al , 2022; Rani and Kaushal, 2022). TOPSIS has become a popular approach owing to its ability to reflect the overall situation of alternatives in a centralized manner.…”

Section: Introductionmentioning

confidence: 99%

Three-parameter interval grey number dynamic TOPSIS method based on comprehensive similarity

Zhang

Shen

2023

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PurposeThree-parameter interval grey numbers (TPIGNs) have been extensively studied as an extended form of interval numbers. However, most existing TPIGN multi-attribute decision-making methods only consider the similarity of positions, ignore the similarity of developmental directions and focus primarily on static evaluation. To address these limitations, in this study, the authors propose a dynamic technique for order preference by similarity to an ideal solution (TOPSIS) based on modified Jaccard similarity and angle similarity for TPIGNs.Design/methodology/approachFirst, the authors extend Jaccard similarity to a TPIGN environment to represent positional similarity. A simple example is provided to illustrate the limitations of the traditional Jaccard similarity. Then, the authors introduce an angle similarity measure to represent developmental directional similarity. Finally, a dynamic TOPSIS model is constructed by incorporating time-series data into conventional two-dimensional static data. Stage weights are obtained by an objective function designed to maximize the amount and minimize the fluctuation of decision information. A quadratic weighting method is adopted to derive the overall evaluation value of alternatives.FindingsTo evaluate the effectiveness of the proposed method, this study takes the pre-assessment of ice disaster and the selection of cooperative enterprises as examples. The authors then provide the results of comparative and sensitivity analyses, which demonstrate the effectiveness and flexibility of the proposed method.Originality/valueThe proposed TOPSIS method in a TPIGN environment can take a more holistic and dynamic perspective for decision-making, which helps mitigate the limitations of single-perspective or static evaluations.

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Transferable graph neural networks with deep alignment attention

Xie

Yang

2023

Information Sciences

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GeoClust: Feature engineering based framework for location-sensitive disaster event detection using AHP-TOPSIS

Cited by 9 publications

References 36 publications

Decision-Making Support in Vehicle Routing Problems: A Review of Recent Literature

Decision-Making Support in Vehicle Routing Problems: A Review of Recent Literature

Three-parameter interval grey number dynamic TOPSIS method based on comprehensive similarity

Transferable graph neural networks with deep alignment attention

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