A DEA-TOPSIS method for multiple criteria decision analysis in emergency management

Chen, Ye; Li, Kevin; Xu, Haiyan; Liu, Sifeng

doi:10.1007/s11518-009-5120-3

Cited by 36 publications

(21 citation statements)

References 35 publications

(24 reference statements)

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“…More recent literature has also shown that decision outcomes can be strengthened by merging the application of DEA with other quantitative approaches such as Artificial Neural Networks [39], the Knapsack problem [36], Analytical Hierarchy Process [34], Analytic Network Process [38], TOPSIS [42,43], and fuzzy logic [34,36].…”

Section: Literature Reviewmentioning

confidence: 99%

A Multi-Criteria Decision-Making Approach That Combines Fuzzy Topsis and Dea Methodologies

Taylan

Alidrisi

Kabli

2014

SAJIE

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Employee selection is a multi-criteria decision-making (MCDM) problem for selecting suitable applicants from a ready pool. The selection aims to make use of their knowledge, relevant skills, and other characteristics to perform a specific job. The aim of this study is to develop a systematic approach for selecting the best candidates among the air traffic controllers (ATCs) for aviation in Saudi Arabia. Three integrated methods were employed for decision-making in this study. First, a fuzzy decision tree was applied to determine the criteria weights, then the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was employed to rank the attributes. In the last step, the Data Envelopment Analysis (DEA) was used to transform the qualitative variables into quantitative equivalences. A survey was conducted by national and international decisionmakers to elicit the necessary information on the criteria and sub-criteria of the air traffic control system. The decision problem was formulated by employing five criteria and ten applicants. The relationship between the fuzzy TOPSIS and fuzzy-weighted average was very positive for decision-making. The outcomes of the fuzzy TOPSIS and DEA encouraged the development of a decision support system for the selection of ATCs. OPSOMMINGDie kies van werknemers vanuit 'n lys van gepaste aansoeke is 'n multi-kriteria besluitnemingsprobleem. Die seleksie se doel is om gebruik te maak van die potensiële werknemers se relevante vaardighede en ander eienskappe om 'n spesifieke taak te verrig. Die doel van hierdie navorsing is om 'n sistematiese benadering, om die beste kandidate vir lugruimbeheerderposisies in Saoedi Arabië te identifiseer, te ontwikkel. Drie geïntegreerde metodes is ingespan vir die besluitneming in hierdie studie. Eerstens is 'n wasige besluitnemingsboom toegepas om die kriteria gewigte te bepaal. Daarna is die wasige tegniek van Orde Voorkeur deur Ooreenkoms tot die Ideale Oplossing toegepas om die kenmerke te rangskik. Laastens is die Data Omvangs Analise gebruik om die kwalitatiewe veranderlikes tot kwantitatiewe gelykhede om te skakel. 'n Peiling is onder nasionale en internasionale besluitnemers geneem om die noodsaaklike inligting rakende die kriteria en sub-kriteria van die lugruimbeheerstelsel te bepaal. Die besluitnemingsvraagstuk is geformuleer deur vyf kriteria en tien aansoekers in te span. Die verhouding tussen die wasige Orde Voorkeur deur Ooreenkoms tot die Ideale Oplossing en wasig-geweegde gemiddeld was besonder positief vir besluitneming. Die resultate van die wasige Orde Voorkeur deur Ooreenkoms tot die Ideale Oplossing en die Data Omvangs Analise moedig die ontwikkeling van 'n besluitneming ondersteuningstelsel vir lugruimbeheerders aan.

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Section: Literature Reviewmentioning

confidence: 99%

A Multi-Criteria Decision-Making Approach That Combines Fuzzy Topsis and Dea Methodologies

Taylan

Alidrisi

Kabli

2014

SAJIE

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“…This numerical example is re-analyzed using the new method, and the results compared with those from VIKOR and TOPSIS. An additional case study, using data from the Emergency Management Australia (EMA) Disasters Database, is presented in [32]. It is based on a refined version of this method, and is recommended as another practical application.…”

Section: Comparative Studiesmentioning

confidence: 99%

An extreme-distance approach to multiple criteria ranking

Chen

Kilgour

Hipel

2011

Mathematical and Computer Modelling

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a b s t r a c tA distance approach based on extreme points, or predefined ideal and anti-ideal points, is proposed to improve on the TOPSIS (Technique for Order Performance [or Ordered Preference] by Similarity to Ideal Solution) method of multiple criteria ranking. Two case studies demonstrate how the analysis procedure works, and provide a basis for comparison of the proposed method to the original TOPSIS and similar methods. In applications, the new method produces results that are generally consistent with the original technique, but offers new features such as a clear interpretation of extreme points, more flexibility in setting extreme points, no normalization distortion, and the ability to handle nonmonotonic criteria.

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“…Multi-criteria decision making (MCDM) methods have therefore been extensively employed to study emergency management, for instance, the Ordered Weighted Averaging (OWA) [2], Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) [3], Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) [4], Analytic Hierarchy Process (AHP) ( [5], [6],and [7]), Analytic Network Process (ANP) ( [8], [9]), Decision Making Trial and Evaluation Laboratory (DEMATEL) [10], Fusion Approach of MCDM (FAMCDM) methods [11] etc. Among these MCDM methods, AHP and ANP are two of the most popular methods for studying emergency management, and usually used to assess the emergency management performance, select the best emergency response alternatives or emergency recovery alternatives and allocate reasonable relief resources etc.…”

Section: Introductionmentioning

confidence: 99%

Data Consistency in Emergency Management

Ergu

Kou

Peng

et al. 2014

INT J COMPUT COMMUN

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Abstract:Timely response is extremely important in emergency management. However, cardinal inconsistent data may exist in a judgment matrix because of the limited expertise, preference conflict as well as the complexity nature of the decision problems. The existing inconsistent data processing models for positive reciprocal matrix either are complicated or dependent on the priority weights, which will delay the decision making process in emergency. In this paper, a geometric mean induced bias matrix (GMIBM), which is only based on the original matrix A, is proposed to quickly identify the most inconsistent data in the judgment matrix. The correctness and effectiveness of the proposed model are proved mathematically and illustrated by two numerical examples. The results show that the proposed model not only preserves most of the original information in matrix A, but also is faster than existing methods.

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A DEA-TOPSIS method for multiple criteria decision analysis in emergency management

Cited by 36 publications

References 35 publications

A Multi-Criteria Decision-Making Approach That Combines Fuzzy Topsis and Dea Methodologies

A Multi-Criteria Decision-Making Approach That Combines Fuzzy Topsis and Dea Methodologies

An extreme-distance approach to multiple criteria ranking

Data Consistency in Emergency Management

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