A ranking method based on DEA and PROMETHEE II (a rank based on DEA &amp; PR.II)

Bagherikahvarin, Maryam; Smet, Yves De

doi:10.1016/j.measurement.2016.04.026

Cited by 30 publications

(16 citation statements)

References 36 publications

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“…Hence, the technology has been named in contemporary literature PROMETHEE GAIA. The number of the studies applying PROMETHEE GAIA method in their research is increasing year after year, which is confirmed by numerous publications [64,65,67,68,[70][71][72][73][74][75][76].…”

Section: Data Collectionmentioning

confidence: 79%

“…MCDM methods provide mathematical models for ranking alternatives based on the selected criteria, clearly and transparently presenting ranking alternative results and synthesis of final results [64,65]. PROMETHEE (Preference Ranking Organization METHod for Enrichment Evaluation) is a kind of MCDM method developed by J. P. Brans and its basic point is comparison based on alignement [66][67][68].…”

Section: Data Collectionmentioning

confidence: 99%

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New Approach to Multi-Criteria Ranking of the Copper Concentrate Smelting Processes based on the PROMETHEE/GAIA Methodology

2019

APH

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Although the production of copper and its usage has been known for thousands of years, the search for the optimal process of its production is still in progress. The removal of the negative impacts of a certain technology could cost more, over a period of time, than the initial investment in the selection of the optimal technology process which would consider these effects. Hence, the selection should be supported by the innovative and modern tools, such as the applying of the multi-criteria analysis. This paper presents the implementation of the PROMETHEE/GAIA methodology for the ranking of the appropriate technological pyrometallurgical smelting process for the copper concentrate based on the eleven parameters which recognize the economic, ecological and technical aspects of the technological process. The implementation of the multi-criteria decision-making presented in this paper can be deemed as a contribution to the decision making tools, that is, to the one who makes a decision on the selection of the appropriate technological facility for smelting of the copper concentrates. The decision-makers faced with the practical need of evaluating and selecting the most appropriate technological process for pyrometallurgical copper extraction will get the greatest benefit from this multi-criteria model. The innovative contribution of this paper is also presented in the obtained model which systematically analyzes the ecological, economic and technical parameters of the copper extraction process.

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Section: Data Collectionmentioning

confidence: 79%

Section: Data Collectionmentioning

confidence: 99%

New Approach to Multi-Criteria Ranking of the Copper Concentrate Smelting Processes based on the PROMETHEE/GAIA Methodology

2019

APH

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“…Despite their implementation being widespread in MCDA, PROMETHEE methods present some drawbacks in their application to real-world decision problems, due to the limitations imposed by their basic assumptions [37]. As a consequence, to overcome these shortcomings, in the last decade many extensions of PROMETHEE methods have been proposed in literature with respect to, among others, weights determination [38], integration with data envelopment analysis [39,40], analytic network process [41] or fuzzy approaches [42,43], recommendations robustness [44], and sorting methods [45].…”

Section: Methodological Backgroundmentioning

confidence: 99%

Ranking of Adaptive Reuse Strategies for Abandoned Industrial Heritage in Vulnerable Contexts: A Multiple Criteria Decision Aiding Approach

2019

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In recent years adaptive reuse has proven to be a promising strategy for preserving cultural heritage. When the adaptive reuse approach is used for cultural heritage, the expected outcome is not only the building protection, but the preservation of its historical and heritage significance, and the trade-off between the retention of symbolic values and the adaptation to new alternative (economically profitable) uses becomes of paramount importance. Decisions on the allocation of resources for cultural heritage preservation or development are based on a set of multiple, often conflicting, criteria, as well on the preferences of various, and not always consensual, stakeholders, who attribute different relative importance to market and non-market effects of adaptive reuse proposals. In this context, multiple criteria approaches provide a proper theoretical and methodological framework to address the complexity which characterizes adaptive reuse strategies of cultural heritage. This paper aims to contribute to this strand of literature by proposing a multicriteria decision aiding approach for ranking adaptive reuse strategies of cultural heritage. In detail, we present a novel application of the Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE) to support the design and implementation of adaptive reuse strategies of abandoned industrial heritage in vulnerable contexts, and evaluate relative tangible and intangible effects. Industrial sites are frequently left to deteriorate, as their preservation is not considered as important as other kinds of heritage structures. Nevertheless, they are characterized by special architectural and technical features as well as by huge spaces suitable to be redeveloped for new uses. The paper focuses on the potential reuse of nine different abandoned buildings located in an industrial valley in the North-West of Italy, with a strong presence of wool and silk factories starting from the 18th century.

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“…Podinovski and Bouzdine-Chameeva (2016) discussed the negative effects of using very low values for lower bounds of weights and suggested a modified DEA model to overcome these. Bagherikahvarin and Smet (2016) derived the restrictions on weights of DEA from an MCDM method. Using PROMETHEE II, they obtained intervals for the weights.…”

Section: Literature Reviewmentioning

confidence: 99%

A new DEA approach to fully rank DMUs with an application to MBA programs

Ekiz

Şakar

2019

Int Trans Operational Res

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Data envelopment analysis (DEA) can be used to evaluate the efficiencies of decision‐making units (DMUs) in various areas like education, healthcare, and energy. Several DEA methods are proposed for this purpose; however, some of these methods cannot provide a full ranking and others often overlook some considerations that arise with special characteristics of DMUs. We propose a new DEA‐based approach to achieve a full ranking of DMUs. Our approach takes various issues into account such as the initial efficiency score of the DMU, the DMUs that should be removed from the set for it to become efficient (if any) and its effects on the efficiency scores of other DMUs. We demonstrate the shortcomings of several other DEA methods and discuss how our approach overcomes these. We apply our approach to evaluate 50 MBA programs from Financial Times 2018 rankings and compare the results with the evaluations of other methods. As opposed to some methods, our approach has the advantage of differentiating between all efficient DMUs as well as inefficient ones. In addition, the results demonstrate that we can achieve a consistent ranking that considers different aspects of the problem setting. The generated scores are also used to sort DMUs in classes of preference.

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A ranking method based on DEA and PROMETHEE II (a rank based on DEA & PR.II)

Cited by 30 publications

References 36 publications

New Approach to Multi-Criteria Ranking of the Copper Concentrate Smelting Processes based on the PROMETHEE/GAIA Methodology

New Approach to Multi-Criteria Ranking of the Copper Concentrate Smelting Processes based on the PROMETHEE/GAIA Methodology

Ranking of Adaptive Reuse Strategies for Abandoned Industrial Heritage in Vulnerable Contexts: A Multiple Criteria Decision Aiding Approach

A new DEA approach to fully rank DMUs with an application to MBA programs

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